Category Archives: artificial intelligence (AI)

Photonic synapses with low power consumption (and a few observations)

This work on brainlike (neuromorphic) computing was announced in a June 30, 2022 Compuscript Ltd news release on EurekAlert,

Photonic synapses with low power consumption and high sensitivity are expected to integrate sensing-memory-preprocessing capabilities

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2022.210069 discusses how photonic synapses with low power consumption and high sensitivity are expected to integrate sensing-memory-preprocessing capabilities.

Neuromorphic photonics/electronics is the future of ultralow energy intelligent computing and artificial intelligence (AI). In recent years, inspired by the human brain, artificial neuromorphic devices have attracted extensive attention, especially in simulating visual perception and memory storage. Because of its advantages of high bandwidth, high interference immunity, ultrafast signal transmission and lower energy consumption, neuromorphic photonic devices are expected to realize real-time response to input data. In addition, photonic synapses can realize non-contact writing strategy, which contributes to the development of wireless communication. The use of low-dimensional materials provides an opportunity to develop complex brain-like systems and low-power memory logic computers. For example, large-scale, uniform and reproducible transition metal dichalcogenides (TMDs) show great potential for miniaturization and low-power biomimetic device applications due to their excellent charge-trapping properties and compatibility with traditional CMOS processes. The von Neumann architecture with discrete memory and processor leads to high power consumption and low efficiency of traditional computing. Therefore, the sensor-memory fusion or sensor-memory- processor integration neuromorphic architecture system can meet the increasingly developing demands of big data and AI for low power consumption and high performance devices. Artificial synaptic devices are the most important components of neuromorphic systems. The performance evaluation of synaptic devices will help to further apply them to more complex artificial neural networks (ANN).

Chemical vapor deposition (CVD)-grown TMDs inevitably introduce defects or impurities, showed a persistent photoconductivity (PPC) effect. TMDs photonic synapses integrating synaptic properties and optical detection capabilities show great advantages in neuromorphic systems for low-power visual information perception and processing as well as brain memory.

The research Group of Optical Detection and Sensing (GODS) have reported a three-terminal photonic synapse based on the large-area, uniform multilayer MoS2 films. The reported device realized ultrashort optical pulse detection within 5 μs and ultralow power consumption about 40 aJ, which means its performance is much better than the current reported properties of photonic synapses. Moreover, it is several orders of magnitude lower than the corresponding parameters of biological synapses, indicating that the reported photonic synapse can be further used for more complex ANN. The photoconductivity of MoS2 channel grown by CVD is regulated by photostimulation signal, which enables the device to simulate short-term synaptic plasticity (STP), long-term synaptic plasticity (LTP), paired-pulse facilitation (PPF) and other synaptic properties. Therefore, the reported photonic synapse can simulate human visual perception, and the detection wavelength can be extended to near infrared light. As the most important system of human learning, visual perception system can receive 80% of learning information from the outside. With the continuous development of AI, there is an urgent need for low-power and high sensitivity visual perception system that can effectively receive external information. In addition, with the assistant of gate voltage, this photonic synapse can simulate the classical Pavlovian conditioning and the regulation of different emotions on memory ability. For example, positive emotions enhance memory ability and negative emotions weaken memory ability. Furthermore, a significant contrast in the strength of STP and LTP based on the reported photonic synapse suggests that it can preprocess the input light signal. These results indicate that the photo-stimulation and backgate control can effectively regulate the conductivity of MoS2 channel layer by adjusting carrier trapping/detrapping processes. Moreover, the photonic synapse presented in this paper is expected to integrate sensing-memory-preprocessing capabilities, which can be used for real-time image detection and in-situ storage, and also provides the possibility to break the von Neumann bottleneck. 

Here’s a link to and a citation for the paper,

Photonic synapses with ultralow energy consumption for artificial visual perception and brain storage by Caihong Li, Wen Du, Yixuan Huang, Jihua Zou, Lingzhi Luo, Song Sun, Alexander O. Govorov, Jiang Wu, Hongxing Xu, Zhiming Wang. Opto-Electron Adv Vol 5, No 9 210069 (2022). doi: 10.29026/oea.2022.210069

This paper is open access.

Observations

I don’t have much to say about the research itself other than, I believe this is the first time I’ve seen a news release about neuromorphic computing research from China.

it’s China that most interests me, especially these bits from the June 30, 2022 Compuscript Ltd news release on EurekAlert,

Group of Optical Detection and Sensing (GODS) [emphasis mine] was established in 2019. It is a research group focusing on compound semiconductors, lasers, photodetectors, and optical sensors. GODS has established a well-equipped laboratory with research facilities such as Molecular Beam Epitaxy system, IR detector test system, etc. GODS is leading several research projects funded by NSFC and National Key R&D Programmes. GODS have published more than 100 research articles in Nature Electronics, Light: Science and Applications, Advanced Materials and other international well-known high-level journals with the total citations beyond 8000.

Jiang Wu obtained his Ph.D. from the University of Arkansas Fayetteville in 2011. After his Ph.D., he joined UESTC as associate professor and later professor. He joined University College London [UCL] as a research associate in 2012 and then lecturer in the Department of Electronic and Electrical Engineering at UCL from 2015 to 2018. He is now a professor at UESTC [University of Electronic Science and Technology of China] [emphases mine]. His research interests include optoelectronic applications of semiconductor heterostructures. He is a Fellow of the Higher Education Academy and Senior Member of IEEE.

Opto-Electronic Advances (OEA) is a high-impact, open access, peer reviewed monthly SCI journal with an impact factor of 9.682 (Journals Citation Reports for IF 2020). Since its launch in March 2018, OEA has been indexed in SCI, EI, DOAJ, Scopus, CA and ICI databases over the time and expanded its Editorial Board to 36 members from 17 countries and regions (average h-index 49). [emphases mine]

The journal is published by The Institute of Optics and Electronics, Chinese Academy of Sciences, aiming at providing a platform for researchers, academicians, professionals, practitioners, and students to impart and share knowledge in the form of high quality empirical and theoretical research papers covering the topics of optics, photonics and optoelectronics.

The research group’s awkward name was almost certainly developed with the rather grandiose acronym, GODS, in mind. I don’t think you could get away with doing this in an English-speaking country as your colleagues would mock you mercilessly.

It’s Jiang Wu’s academic and work history that’s of most interest as it might provide insight into China’s Young Thousand Talents program. A January 5, 2023 American Association for the Advancement of Science (AAAS) news release describes the program,

In a systematic evaluation of China’s Young Thousand Talents (YTT) program, which was established in 2010, researchers find that China has been successful in recruiting and nurturing high-caliber Chinese scientists who received training abroad. Many of these individuals outperform overseas peers in publications and access to funding, the study shows, largely due to access to larger research teams and better research funding in China. Not only do the findings demonstrate the program’s relative success, but they also hold policy implications for the increasing number of governments pursuing means to tap expatriates for domestic knowledge production and talent development. China is a top sender of international students to United States and European Union science and engineering programs. The YTT program was created to recruit and nurture the productivity of high-caliber, early-career, expatriate scientists who return to China after receiving Ph.Ds. abroad. Although there has been a great deal of international attention on the YTT, some associated with the launch of the U.S.’s controversial China Initiative and federal investigations into academic researchers with ties to China, there has been little evidence-based research on the success, impact, and policy implications of the program itself. Dongbo Shi and colleagues evaluated the YTT program’s first 4 cohorts of scholars and compared their research productivity to that of their peers that remained overseas. Shi et al. found that China’s YTT program successfully attracted high-caliber – but not top-caliber – scientists. However, those young scientists that did return outperformed others in publications across journal-quality tiers – particularly in last-authored publications. The authors suggest that this is due to YTT scholars’ greater access to larger research teams and better research funding in China. The authors say the dearth of such resources in the U.S. and E.U. “may not only expedite expatriates’ return decisions but also motivate young U.S.- and E.U.-born scientists to seek international research opportunities.” They say their findings underscore the need for policy adjustments to allocate more support for young scientists.

Here’s a link to and a citation for the paper,

Has China’s Young Thousand Talents program been successful in recruiting and nurturing top-caliber scientists? by Dongbo Shi, Weichen Liu, and Yanbo Wang. Science 5 Jan 2023 Vol 379, Issue 6627 pp. 62-65 DOI: 10.1126/science.abq1218

This paper is behind a paywall.

Kudos to the folks behind China’s Young Thousands Talents program! Jiang Wu’s career appears to be a prime example of the program’s success. Perhaps Canadian policy makers will be inspired.

FrogHeart’s 2022 comes to an end as 2023 comes into view

I look forward to 2023 and hope it will be as stimulating as 2022 proved to be. Here’s an overview of the year that was on this blog:

Sounds of science

It seems 2022 was the year that science discovered the importance of sound and the possibilities of data sonification. Neither is new but this year seemed to signal a surge of interest or maybe I just happened to stumble onto more of the stories than usual.

This is not an exhaustive list, you can check out my ‘Music’ category for more here. I have tried to include audio files with the postings but it all depends on how accessible the researchers have made them.

Aliens on earth: machinic biology and/or biological machinery?

When I first started following stories in 2008 (?) about technology or machinery being integrated with the human body, it was mostly about assistive technologies such as neuroprosthetics. You’ll find most of this year’s material in the ‘Human Enhancement’ category or you can search the tag ‘machine/flesh’.

However, the line between biology and machine became a bit more blurry for me this year. You can see what’s happening in the titles listed below (you may recognize the zenobot story; there was an earlier version of xenobots featured here in 2021):

This was the story that shook me,

Are the aliens going to come from outer space or are we becoming the aliens?

Brains (biological and otherwise), AI, & our latest age of anxiety

As we integrate machines into our bodies, including our brains, there are new issues to consider:

  • Going blind when your neural implant company flirts with bankruptcy (long read) April 5, 2022 posting
  • US National Academies Sept. 22-23, 2022 workshop on techno, legal & ethical issues of brain-machine interfaces (BMIs) September 21, 2022 posting

I hope the US National Academies issues a report on their “Brain-Machine and Related Neural Interface Technologies: Scientific, Technical, Ethical, and Regulatory Issues – A Workshop” for 2023.

Meanwhile the race to create brainlike computers continues and I have a number of posts which can be found under the category of ‘neuromorphic engineering’ or you can use these search terms ‘brainlike computing’ and ‘memristors’.

On the artificial intelligence (AI) side of things, I finally broke down and added an ‘artificial intelligence (AI) category to this blog sometime between May and August 2021. Previously, I had used the ‘robots’ category as a catchall. There are other stories but these ones feature public engagement and policy (btw, it’s a Canadian Science Policy Centre event), respectively,

  • “The “We are AI” series gives citizens a primer on AI” March 23, 2022 posting
  • “Age of AI and Big Data – Impact on Justice, Human Rights and Privacy Zoom event on September 28, 2022 at 12 – 1:30 pm EDT” September 16, 2022 posting

These stories feature problems, which aren’t new but seem to be getting more attention,

While there have been issues over AI, the arts, and creativity previously, this year they sprang into high relief. The list starts with my two-part review of the Vancouver Art Gallery’s AI show; I share most of my concerns in part two. The third post covers intellectual property issues (mostly visual arts but literary arts get a nod too). The fourth post upends the discussion,

  • “Mad, bad, and dangerous to know? Artificial Intelligence at the Vancouver (Canada) Art Gallery (1 of 2): The Objects” July 28, 2022 posting
  • “Mad, bad, and dangerous to know? Artificial Intelligence at the Vancouver (Canada) Art Gallery (2 of 2): Meditations” July 28, 2022 posting
  • “AI (artificial intelligence) and art ethics: a debate + a Botto (AI artist) October 2022 exhibition in the Uk” October 24, 2022 posting
  • Should AI algorithms get patents for their inventions and is anyone talking about copyright for texts written by AI algorithms? August 30, 2022 posting

Interestingly, most of the concerns seem to be coming from the visual and literary arts communities; I haven’t come across major concerns from the music community. (The curious can check out Vancouver’s Metacreation Lab for Artificial Intelligence [located on a Simon Fraser University campus]. I haven’t seen any cautionary or warning essays there; it’s run by an AI and creativity enthusiast [professor Philippe Pasquier]. The dominant but not sole focus is art, i.e., music and AI.)

There is a ‘new kid on the block’ which has been attracting a lot of attention this month. If you’re curious about the latest and greatest AI anxiety,

  • Peter Csathy’s December 21, 2022 Yahoo News article (originally published in The WRAP) makes this proclamation in the headline “Chat GPT Proves That AI Could Be a Major Threat to Hollywood Creatives – and Not Just Below the Line | PRO Insight”
  • Mouhamad Rachini’s December 15, 2022 article for the Canadian Broadcasting Corporation’s (CBC) online news overs a more generalized overview of the ‘new kid’ along with an embedded CBC Radio file which runs approximately 19 mins. 30 secs. It’s titled “ChatGPT a ‘landmark event’ for AI, but what does it mean for the future of human labour and disinformation?” The chat bot’s developer, OpenAI, has been mentioned here many times including the previously listed July 28, 2022 posting (part two of the VAG review) and the October 24, 2022 posting.

Opposite world (quantum physics in Canada)

Quantum computing made more of an impact here (my blog) than usual. it started in 2021 with the announcement of a National Quantum Strategy in the Canadian federal government budget for that year and gained some momentum in 2022:

  • “Quantum Mechanics & Gravity conference (August 15 – 19, 2022) launches Vancouver (Canada)-based Quantum Gravity Institute and more” July 26, 2022 posting Note: This turned into one of my ‘in depth’ pieces where I comment on the ‘Canadian quantum scene’ and highlight the appointment of an expert panel for the Council of Canada Academies’ report on Quantum Technologies.
  • “Bank of Canada and Multiverse Computing model complex networks & cryptocurrencies with quantum computing” July 25, 2022 posting
  • “Canada, quantum technology, and a public relations campaign?” December 29, 2022 posting

This one was a bit of a puzzle with regard to placement in this end-of-year review, it’s quantum but it’s also about brainlike computing

It’s getting hot in here

Fusion energy made some news this year.

There’s a Vancouver area company, General Fusion, highlighted in both postings and the October posting includes an embedded video of Canadian-born rapper Baba Brinkman’s “You Must LENR” [L ow E nergy N uclear R eactions or sometimes L attice E nabled N anoscale R eactions or Cold Fusion or CANR (C hemically A ssisted N uclear R eactions)].

BTW, fusion energy can generate temperatures up to 150 million degrees Celsius.

Ukraine, science, war, and unintended consequences

Here’s what you might expect,

These are the unintended consequences (from Rachel Kyte’s, Dean of the Fletcher School, Tufts University, December 26, 2022 essay on The Conversation [h/t December 27, 2022 news item on phys.org]), Note: Links have been removed,

Russian President Vladimir Putin’s war on Ukraine has reverberated through Europe and spread to other countries that have long been dependent on the region for natural gas. But while oil-producing countries and gas lobbyists are arguing for more drilling, global energy investments reflect a quickening transition to cleaner energy. [emphasis mine]

Call it the Putin effect – Russia’s war is speeding up the global shift away from fossil fuels.

In December [2022?], the International Energy Agency [IEA] published two important reports that point to the future of renewable energy.

First, the IEA revised its projection of renewable energy growth upward by 30%. It now expects the world to install as much solar and wind power in the next five years as it installed in the past 50 years.

The second report showed that energy use is becoming more efficient globally, with efficiency increasing by about 2% per year. As energy analyst Kingsmill Bond at the energy research group RMI noted, the two reports together suggest that fossil fuel demand may have peaked. While some low-income countries have been eager for deals to tap their fossil fuel resources, the IEA warns that new fossil fuel production risks becoming stranded, or uneconomic, in the next 20 years.

Kyte’s essay is not all ‘sweetness and light’ but it does provide a little optimism.

Kudos, nanotechnology, culture (pop & otherwise), fun, and a farewell in 2022

This one was a surprise for me,

Sometimes I like to know where the money comes from and I was delighted to learn of the Ărramăt Project funded through the federal government’s New Frontiers in Research Fund (NFRF). Here’s more about the Ărramăt Project from the February 14, 2022 posting,

“The Ărramăt Project is about respecting the inherent dignity and interconnectedness of peoples and Mother Earth, life and livelihood, identity and expression, biodiversity and sustainability, and stewardship and well-being. Arramăt is a word from the Tamasheq language spoken by the Tuareg people of the Sahel and Sahara regions which reflects this holistic worldview.” (Mariam Wallet Aboubakrine)

Over 150 Indigenous organizations, universities, and other partners will work together to highlight the complex problems of biodiversity loss and its implications for health and well-being. The project Team will take a broad approach and be inclusive of many different worldviews and methods for research (i.e., intersectionality, interdisciplinary, transdisciplinary). Activities will occur in 70 different kinds of ecosystems that are also spiritually, culturally, and economically important to Indigenous Peoples.

The project is led by Indigenous scholars and activists …

Kudos to the federal government and all those involved in the Salmon science camps, the Ărramăt Project, and other NFRF projects.

There are many other nanotechnology posts here but this appeals to my need for something lighter at this point,

  • “Say goodbye to crunchy (ice crystal-laden) in ice cream thanks to cellulose nanocrystals (CNC)” August 22, 2022 posting

The following posts tend to be culture-related, high and/or low but always with a science/nanotechnology edge,

Sadly, it looks like 2022 is the last year that Ada Lovelace Day is to be celebrated.

… this year’s Ada Lovelace Day is the final such event due to lack of financial backing. Suw Charman-Anderson told the BBC [British Broadcasting Corporation] the reason it was now coming to an end was:

You can read more about it here:

In the rearview mirror

A few things that didn’t fit under the previous heads but stood out for me this year. Science podcasts, which were a big feature in 2021, also proliferated in 2022. I think they might have peaked and now (in 2023) we’ll see what survives.

Nanotechnology, the main subject on this blog, continues to be investigated and increasingly integrated into products. You can search the ‘nanotechnology’ category here for posts of interest something I just tried. It surprises even me (I should know better) how broadly nanotechnology is researched and applied.

If you want a nice tidy list, Hamish Johnston in a December 29, 2022 posting on the Physics World Materials blog has this “Materials and nanotechnology: our favourite research in 2022,” Note: Links have been removed,

“Inherited nanobionics” makes its debut

The integration of nanomaterials with living organisms is a hot topic, which is why this research on “inherited nanobionics” is on our list. Ardemis Boghossian at EPFL [École polytechnique fédérale de Lausanne] in Switzerland and colleagues have shown that certain bacteria will take up single-walled carbon nanotubes (SWCNTs). What is more, when the bacteria cells split, the SWCNTs are distributed amongst the daughter cells. The team also found that bacteria containing SWCNTs produce a significantly more electricity when illuminated with light than do bacteria without nanotubes. As a result, the technique could be used to grow living solar cells, which as well as generating clean energy, also have a negative carbon footprint when it comes to manufacturing.

Getting to back to Canada, I’m finding Saskatchewan featured more prominently here. They do a good job of promoting their science, especially the folks at the Canadian Light Source (CLS), Canada’s synchrotron, in Saskatoon. Canadian live science outreach events seeming to be coming back (slowly). Cautious organizers (who have a few dollars to spare) are also enthusiastic about hybrid events which combine online and live outreach.

After what seems like a long pause, I’m stumbling across more international news, e.g. “Nigeria and its nanotechnology research” published December 19, 2022 and “China and nanotechnology” published September 6, 2022. I think there’s also an Iran piece here somewhere.

With that …

Making resolutions in the dark

Hopefully this year I will catch up with the Council of Canadian Academies (CCA) output and finally review a few of their 2021 reports such as Leaps and Boundaries; a report on artificial intelligence applied to science inquiry and, perhaps, Powering Discovery; a report on research funding and Natural Sciences and Engineering Research Council of Canada.

Given what appears to a renewed campaign to have germline editing (gene editing which affects all of your descendants) approved in Canada, I might even reach back to a late 2020 CCA report, Research to Reality; somatic gene and engineered cell therapies. it’s not the same as germline editing but gene editing exists on a continuum.

For anyone who wants to see the CCA reports for themselves they can be found here (both in progress and completed).

I’m also going to be paying more attention to how public relations and special interests influence what science is covered and how it’s covered. In doing this 2022 roundup, I noticed that I featured an overview of fusion energy not long before the breakthrough. Indirect influence on this blog?

My post was precipitated by an article by Alex Pasternak in Fast Company. I’m wondering what precipitated Alex Pasternack’s interest in fusion energy since his self-description on the Huffington Post website states this “… focus on the intersections of science, technology, media, politics, and culture. My writing about those and other topics—transportation, design, media, architecture, environment, psychology, art, music … .”

He might simply have received a press release that stimulated his imagination and/or been approached by a communications specialist or publicists with an idea. There’s a reason for why there are so many public relations/media relations jobs and agencies.

Que sera, sera (Whatever will be, will be)

I can confidently predict that 2023 has some surprises in store. I can also confidently predict that the European Union’s big research projects (1B Euros each in funding for the Graphene Flagship and Human Brain Project over a ten year period) will sunset in 2023, ten years after they were first announced in 2013. Unless, the powers that be extend the funding past 2023.

I expect the Canadian quantum community to provide more fodder for me in the form of a 2023 report on Quantum Technologies from the Council of Canadian academies, if nothing else otherwise.

I’ve already featured these 2023 science events but just in case you missed them,

  • 2023 Preview: Bill Nye the Science Guy’s live show and Marvel Avengers S.T.A.T.I.O.N. (Scientific Training And Tactical Intelligence Operative Network) coming to Vancouver (Canada) November 24, 2022 posting
  • September 2023: Auckland, Aotearoa New Zealand set to welcome women in STEM (science, technology, engineering, and mathematics) November 15, 2022 posting

Getting back to this blog, it may not seem like a new year during the first few weeks of 2023 as I have quite the stockpile of draft posts. At this point I have drafts that are dated from June 2022 and expect to be burning through them so as not to fall further behind but will be interspersing them, occasionally, with more current posts.

Most importantly: a big thank you to everyone who drops by and reads (and sometimes even comments) on my posts!!! it’s very much appreciated and on that note: I wish you all the best for 2023.

Kempner Institute for the Study of Natural and Artificial Intelligence launched at Harvard University and University of Manchester pushes the boundaries of smart robotics and AI

Before getting to the two news items, it might be a good idea to note that ‘artificial intelligence (AI)’ and ‘robot’ are not synonyms although they are often used that way, even by people who should know better. (sigh … I do it too)

A robot may or may not be animated with artificial intelligence while artificial intelligence algorithms may be installed on a variety of devices such as a phone or a computer or a thermostat or a … .

It’s something to bear in mind when reading about the two new institutions being launched. Now, on to Harvard University.

Kempner Institute for the Study of Natural and Artificial Intelligence

A September 23, 2022 Chan Zuckerberg Initiative (CZI) news release (also on EurekAlert) announces a symposium to launch a new institute close to Mark Zuckerberg’s heart,

On Thursday [September 22, 2022], leadership from the Chan Zuckerberg Initiative (CZI) and Harvard University celebrated the launch of the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University with a symposium on Harvard’s campus. Speakers included CZI Head of Science Stephen Quake, President of Harvard University Lawrence Bacow, Provost of Harvard University Alan Garber, and Kempner Institute co-directors Bernardo Sabatini and Sham Kakade. The event also included remarks and panels from industry leaders in science, technology, and artificial intelligence, including Bill Gates, Eric Schmidt, Andy Jassy, Daniel Huttenlocher, Sam Altman, Joelle Pineau, Sangeeta Bhatia, and Yann LeCun, among many others.

The Kempner Institute will seek to better understand the basis of intelligence in natural and artificial systems. Its bold premise is that the two fields are intimately interconnected; the next generation of AI will require the same principles that our brains use for fast, flexible natural reasoning, and understanding how our brains compute and reason requires theories developed for AI. The Kempner Institute will study AI systems, including artificial neural networks, to develop both principled theories [emphasis mine] and a practical understanding of how these systems operate and learn. It will also focus on research topics such as learning and memory, perception and sensation, brain function, and metaplasticity. The Institute will recruit and train future generations of researchers from undergraduates and graduate students to post-docs and faculty — actively recruiting from underrepresented groups at every stage of the pipeline — to study intelligence from biological, cognitive, engineering, and computational perspectives.

CZI Co-Founder and Co-CEO Mark Zuckerberg [chairman and chief executive officer of Meta/Facebook] said: “The Kempner Institute will be a one-of-a-kind institute for studying intelligence and hopefully one that helps us discover what intelligent systems really are, how they work, how they break and how to repair them. There’s a lot of exciting implications because once you understand how something is supposed to work and how to repair it once it breaks, you can apply that to the broader mission the Chan Zuckerberg Initiative has to empower scientists to help cure, prevent or manage all diseases.”

CZI Co-Founder and Co-CEO Priscilla Chan said: “Just attending this school meant the world to me. But to stand on this stage and to be able to give something back is truly a dream come true … All of this progress starts with building one fundamental thing: a Kempner community that’s diverse, multi-disciplinary and multi-generational, because incredible ideas can come from anyone. If you bring together people from all different disciplines to look at a problem and give them permission to articulate their perspective, you might start seeing insights or solutions in a whole different light. And those new perspectives lead to new insights and discoveries and generate new questions that can lead an entire field to blossom. So often, that momentum is what breaks the dam and tears down old orthodoxies, unleashing new floods of new ideas that allow us to progress together as a society.”

CZI Head of Science Stephen Quake said: “It’s an honor to partner with Harvard in building this extraordinary new resource for students and science. This is a once-in-a-generation moment for life sciences and medicine. We are living in such an extraordinary and exciting time for science. Many breakthrough discoveries are going to happen not only broadly but right here on this campus and at this institute.”

CZI’s 10-year vision is to advance research and develop technologies to observe, measure, and analyze any biological process within the human body — across spatial scales and in real time. CZI’s goal is to accelerate scientific progress by funding scientific research to advance entire fields; working closely with scientists and engineers at partner institutions like the Chan Zuckerberg Biohub and Chan Zuckerberg Institute for Advanced Biological Imaging to do the research that can’t be done in conventional environments; and building and democratizing next-generation software and hardware tools to drive biological insights and generate more accurate and biologically important sources of data.

President of Harvard University Lawrence Bacow said: “Here we are with this incredible opportunity that Priscilla Chan and Mark Zuckerberg have given us to imagine taking what we know about the brain, neuroscience and how to model intelligence and putting them together in ways that can inform both, and can truly advance our understanding of intelligence from multiple perspectives.”

Kempner Institute Co-Director and Gordon McKay Professor of Computer Science and of Statistics at the Harvard John A. Paulson School of Engineering and Applied Sciences Sham Kakade said: “Now we begin assembling a world-leading research and educational program at Harvard that collectively tries to understand the fundamental mechanisms of intelligence and seeks to apply these new technologies for the benefit of humanity … We hope to create a vibrant environment for all of us to engage in broader research questions … We want to train the next generation of leaders because those leaders will go on to do the next set of great things.”

Kempner Institute Co-Director and the Alice and Rodman W. Moorhead III Professor of Neurobiology at Harvard Medical School Bernardo Sabatini said: “We’re blending research, education and computation to nurture, raise up and enable any scientist who is interested in unraveling the mysteries of the brain. This field is a nascent and interdisciplinary one, so we’re going to have to teach neuroscience to computational biologists, who are going to have to teach machine learning to cognitive scientists and math to biologists. We’re going to do whatever is necessary to help each individual thrive and push the field forward … Success means we develop mathematical theories that explain how our brains compute and learn, and these theories should be specific enough to be testable and useful enough to start to explain diseases like schizophrenia, dyslexia or autism.”

About the Chan Zuckerberg Initiative

The Chan Zuckerberg Initiative was founded in 2015 to help solve some of society’s toughest challenges — from eradicating disease and improving education, to addressing the needs of our communities. Through collaboration, providing resources and building technology, our mission is to help build a more inclusive, just and healthy future for everyone. For more information, please visit chanzuckerberg.com.

Principled theories, eh. I don’t see a single mention of ethicists or anyone in the social sciences or the humanities or the arts. How are scientists and engineers who have no training in or education in or, even, an introduction to ethics or social impacts or psychology going to manage this?

Mark Zuckerberg’s approach to these issues was something along the lines of “it’s easier to ask for forgiveness than to ask for permission.” I understand there have been changes but it took far too long to recognize the damage let alone attempt to address it.

If you want to gain a little more insight into the Kempner Institute, there’s a December 7, 2021 article by Alvin Powell announcing the institute for the Harvard Gazette,

The institute will be funded by a $500 million gift from Priscilla Chan and Mark Zuckerberg, which was announced Tuesday [December 7, 2021] by the Chan Zuckerberg Initiative. The gift will support 10 new faculty appointments, significant new computing infrastructure, and resources to allow students to flow between labs in pursuit of ideas and knowledge. The institute’s name honors Zuckerberg’s mother, Karen Kempner Zuckerberg, and her parents — Zuckerberg’s grandparents — Sidney and Gertrude Kempner. Chan and Zuckerberg have given generously to Harvard in the past, supporting students, faculty, and researchers in a range of areas, including around public service, literacy, and cures.

“The Kempner Institute at Harvard represents a remarkable opportunity to bring together approaches and expertise in biological and cognitive science with machine learning, statistics, and computer science to make real progress in understanding how the human brain works to improve how we address disease, create new therapies, and advance our understanding of the human body and the world more broadly,” said President Larry Bacow.

Q&A

Bernardo Sabatini and Sham Kakade [Institute co-directors]

GAZETTE: Tell me about the new institute. What is its main reason for being?

SABATINI: The institute is designed to take from two fields and bring them together, hopefully to create something that’s essentially new, though it’s been tried in a couple of places. Imagine that you have over here cognitive scientists and neurobiologists who study the human brain, including the basic biological mechanisms of intelligence and decision-making. And then over there, you have people from computer science, from mathematics and statistics, who study artificial intelligence systems. Those groups don’t talk to each other very much.

We want to recruit from both populations to fill in the middle and to create a new population, through education, through graduate programs, through funding programs — to grow from academic infancy — those equally versed in neuroscience and in AI systems, who can be leaders for the next generation.

Over the millions of years that vertebrates have been evolving, the human brain has developed specializations that are fundamental for learning and intelligence. We need to know what those are to understand their benefits and to ask whether they can make AI systems better. At the same time, as people who study AI and machine learning (ML) develop mathematical theories as to how those systems work and can say that a network of the following structure with the following properties learns by calculating the following function, then we can take those theories and ask, “Is that actually how the human brain works?”

KAKADE: There’s a question of why now? In the technological space, the advancements are remarkable even to me, as a researcher who knows how these things are being made. I think there’s a long way to go, but many of us feel that this is the right time to study intelligence more broadly. You might also ask: Why is this mission unique and why is this institute different from what’s being done in academia and in industry? Academia is good at putting out ideas. Industry is good at turning ideas into reality. We’re in a bit of a sweet spot. We have the scale to study approaches at a very different level: It’s not going to be just individual labs pursuing their own ideas. We may not be as big as the biggest companies, but we can work on the types of problems that they work on, such as having the compute resources to work on large language models. Industry has exciting research, but the spectrum of ideas produced is very different, because they have different objectives.

For the die-hards, there’s a September 23, 2022 article by Clea Simon in Harvard Gazette, which updates the 2021 story,

Next, Manchester, England.

Manchester Centre for Robotics and AI

Robotots take a break at a lab at The University of Manchester – picture courtesy of Marketing Manchester [downloaded from https://www.manchester.ac.uk/discover/news/manchester-ai-summit-aims-to-attract-experts-in-advanced-engineering-and-robotics/]

A November 22, 2022 University of Manchester press release (also on EurekAlert) announces both a meeting and a new centre, Note: Links to the Centre have been retained; all others have been removed,

How humans and super smart robots will live and work together in the future will be among the key issues being scrutinised by experts at a new centre of excellence for AI and autonomous machines based at The University of Manchester.

The Manchester Centre for Robotics and AI will be a new specialist multi-disciplinary centre to explore developments in smart robotics through the lens of artificial intelligence (AI) and autonomous machinery.

The University of Manchester has built a modern reputation of excellence in AI and robotics, partly based on the legacy of pioneering thought leadership begun in this field in Manchester by legendary codebreaker Alan Turing.

Manchester’s new multi-disciplinary centre is home to world-leading research from across the academic disciplines – and this group will hold its first conference on Wednesday, Nov 23, at the University’s new engineering and materials facilities.

A  highlight will be a joint talk by robotics expert Dr Andy Weightman and theologian Dr Scott Midson which is expected to put a spotlight on ‘posthumanism’, a future world where humans won’t be the only highly intelligent decision-makers.

Dr Weightman, who researches home-based rehabilitation robotics for people with neurological impairment, and Dr Midson, who researches theological and philosophical critiques of posthumanism, will discuss how interdisciplinary research can help with the special challenges of rehabilitation robotics – and, ultimately, what it means to be human “in the face of the promises and challenges of human enhancement through robotic and autonomous machines”.

Other topics that the centre will have a focus on will include applications of robotics in extreme environments.

For the past decade, a specialist Manchester team led by Professor Barry Lennox has designed robots to work safely in nuclear decommissioning sites in the UK. A ground-breaking robot called Lyra that has been developed by Professor Lennox’s team – and recently deployed at the Dounreay site in Scotland, the “world’s deepest nuclear clean up site” – has been listed in Time Magazine’s Top 200 innovations of 2022.

Angelo Cangelosi, Professor of Machine Learning and Robotics at Manchester, said the University offers a world-leading position in the field of autonomous systems – a technology that will be an integral part of our future world. 

Professor Cangelosi, co-Director of Manchester’s Centre for Robotics and AI, said: “We are delighted to host our inaugural conference which will provide a special showcase for our diverse academic expertise to design robotics for a variety of real world applications.

“Our research and innovation team are at the interface between robotics, autonomy and AI – and their knowledge is drawn from across the University’s disciplines, including biological and medical sciences – as well the humanities and even theology. [emphases mine]

“This rich diversity offers Manchester a distinctive approach to designing robots and autonomous systems for real world applications, especially when combined with our novel use of AI-based knowledge.”

Delegates will have a chance to observe a series of robots and autonomous machines being demoed at the new conference.

The University of Manchester’s Centre for Robotics and AI will aim to: 

  • design control systems with a focus on bio-inspired solutions to mechatronics, eg the use of biomimetic sensors, actuators and robot platforms; 
  • develop new software engineering and AI methodologies for verification in autonomous systems, with the aim to design trustworthy autonomous systems; 
  • research human-robot interaction, with a pioneering focus on the use of brain-inspired approaches [emphasis mine] to robot control, learning and interaction; and 
  • research the ethics and human-centred robotics issues, for the understanding of the impact of the use of robots and autonomous systems with individuals and society. 

In some ways, the Kempner Institute and the Manchester Centre for Robotics and AI have very similar interests, especially where the brain is concerned. What fascinates me is the Manchester Centre’s inclusion of theologian Dr Scott Midson and the discussion (at the meeting) of ‘posthumanism’. The difference is between actual engagement at the symposium (the centre) and mere mention in a news release (the institute).

I wish the best for both institutions.

AI (artificial intelligence) and art ethics: a debate + a Botto (AI artist) October 2022 exhibition in the Uk

Who is an artist? What is an artist? Can everyone be an artist? These are the kinds of questions you can expect with the rise of artificially intelligent artists/collaborators. Of course, these same questions have been asked many times before the rise of AI (artificial intelligence) agents/programs in the field of visual art. Each time the questions are raised is an opportunity to examine our beliefs from a different perspective. And, not to be forgotten, there are questions about money.

The shock

First, the ‘art’,

The winning work. Colorado State Fair 2022. Screengrab from Discord [downloaded from https://www.artnews.com/art-news/news/colorado-state-fair-ai-generated-artwork-controversy-1234638022/]

Shanti Escalante-De Mattei’s September 1, 2022 article for ArtNews.com provides an overview of the latest AI art controversy (Note: A link has been removed),

The debate around AI art went viral once again when a man won first place at the Colorado State Fair’s art competition in the digital category with a work he made using text-to-image AI generator Midjourney.

Twitter user and digital artist Genel Jumalon tweeted out a screenshot from a Discord channel in which user Sincarnate, aka game designer Jason Allen, celebrated his win at the fair. Jumalon wrote, “Someone entered an art competition with an AI-generated piece and won the first prize. Yeah that’s pretty fucking shitty.”

The comments on the post range from despair and anger as artists, both digital and traditional, worry that their livelihoods might be at stake after years of believing that creative work would be safe from AI-driven automation. [emphasis mine]

Rachel Metz’s September 3, 2022 article for CNN provides more details about how the work was generated (Note: Links have been removed),

Jason M. Allen was almost too nervous to enter his first art competition. Now, his award-winning image is sparking controversy about whether art can be generated by a computer, and what, exactly, it means to be an artist.

In August [2022], Allen, a game designer who lives in Pueblo West, Colorado, won first place in the emerging artist division’s “digital arts/digitally-manipulated photography” category at the Colorado State Fair Fine Arts Competition. His winning image, titled “Théâtre D’opéra Spatial” (French for “Space Opera Theater”), was made with Midjourney — an artificial intelligence system that can produce detailed images when fed written prompts. A $300 prize accompanied his win.

Allen’s winning image looks like a bright, surreal cross between a Renaissance and steampunk painting. It’s one of three such images he entered in the competition. In total, 11 people entered 18 pieces of art in the same category in the emerging artist division.

The definition for the category in which Allen competed states that digital art refers to works that use “digital technology as part of the creative or presentation process.” Allen stated that Midjourney was used to create his image when he entered the contest, he said.

The newness of these tools, how they’re used to produce images, and, in some cases, the gatekeeping for access to some of the most powerful ones has led to debates about whether they can truly make art or assist humans in making art.

This came into sharp focus for Allen not long after his win. Allen had posted excitedly about his win on Midjourney’s Discord server on August 25 [2022], along with pictures of his three entries; it went viral on Twitter days later, with many artists angered by Allen’s win because of his use of AI to create the image, as a story by Vice’s Motherboard reported earlier this week.

“This sucks for the exact same reason we don’t let robots participate in the Olympics,” one Twitter user wrote.

“This is the literal definition of ‘pressed a few buttons to make a digital art piece’,” another Tweeted. “AI artwork is the ‘banana taped to the wall’ of the digital world now.”

Yet while Allen didn’t use a paintbrush to create his winning piece, there was plenty of work involved, he said.

“It’s not like you’re just smashing words together and winning competitions,” he said.

You can feed a phrase like “an oil painting of an angry strawberry” to Midjourney and receive several images from the AI system within seconds, but Allen’s process wasn’t that simple. To get the final three images he entered in the competition, he said, took more than 80 hours.

First, he said, he played around with phrasing that led Midjourney to generate images of women in frilly dresses and space helmets — he was trying to mash up Victorian-style costuming with space themes, he said. Over time, with many slight tweaks to his written prompt (such as to adjust lighting and color harmony), he created 900 iterations of what led to his final three images. He cleaned up those three images in Photoshop, such as by giving one of the female figures in his winning image a head with wavy, dark hair after Midjourney had rendered her headless. Then he ran the images through another software program called Gigapixel AI that can improve resolution and had the images printed on canvas at a local print shop.

Ars Technica has run a number of articles on the subject of Art and AI, Benj Edwards in an August 31, 2022 article seems to have been one of the first to comment on Jason Allen’s win (Note 1: Links have been removed; Note 2: Look at how Edwards identifies Jason Allen as an artist),

A synthetic media artist named Jason Allen entered AI-generated artwork into the Colorado State Fair fine arts competition and announced last week that he won first place in the Digital Arts/Digitally Manipulated Photography category, Vice reported Wednesday [August 31, 2022?] based on a viral tweet.

Allen’s victory prompted lively discussions on Twitter, Reddit, and the Midjourney Discord server about the nature of art and what it means to be an artist. Some commenters think human artistry is doomed thanks to AI and that all artists are destined to be replaced by machines. Others think art will evolve and adapt with new technologies that come along, citing synthesizers in music. It’s a hot debate that Wired covered in July [2022].

It’s worth noting that the invention of the camera in the 1800s prompted similar criticism related to the medium of photography, since the camera seemingly did all the work compared to an artist that labored to craft an artwork by hand with a brush or pencil. Some feared that painters would forever become obsolete with the advent of color photography. In some applications, photography replaced more laborious illustration methods (such as engraving), but human fine art painters are still around today.

Benj Edwards in a September 12, 2022 article for Ars Technica examines how some art communities are responding (Note: Links have been removed),

Confronted with an overwhelming amount of artificial-intelligence-generated artwork flooding in, some online art communities have taken dramatic steps to ban or curb its presence on their sites, including Newgrounds, Inkblot Art, and Fur Affinity, according to Andy Baio of Waxy.org.

Baio, who has been following AI art ethics closely on his blog, first noticed the bans and reported about them on Friday [Sept. 9, 2022?]. …

The arrival of widely available image synthesis models such as Midjourney and Stable Diffusion has provoked an intense online battle between artists who view AI-assisted artwork as a form of theft (more on that below) and artists who enthusiastically embrace the new creative tools.

… a quickly evolving debate about how art communities (and art professionals) can adapt to software that can potentially produce unlimited works of beautiful art at a rate that no human working without the tools could match.

A few weeks ago, some artists began discovering their artwork in the Stable Diffusion data set, and they weren’t happy about it. Charlie Warzel wrote a detailed report about these reactions for The Atlantic last week [September 7, 2022]. With battle lines being drawn firmly in the sand and new AI creativity tools coming out steadily, this debate will likely continue for some time to come.

Filthy lucre becomes more prominent in the conversation

Lizzie O’Leary in a September 12, 2022 article for Fast Company presents a transcript of an interview (from the TBD podcast) she conducted with Drew Harwell, tech reporter covering A.I. for Washington Post) about the ‘Jason Allen’ win,

I’m struck by how quickly these art A.I.s are advancing. DALL-E was released in January of last year and there were some pretty basic images. And then, a year later, DALL-E 2 is using complex, faster methods. Midjourney, the one Jason Allen used, has a feature that allows you to upscale and downscale images. Where is this sudden supply and demand for A.I. art coming from?

You could look back to five years ago when they had these text-to-image generators and the output would be really crude. You could sort of see what the A.I. was trying to get at, but we’ve only really been able to cross that photorealistic uncanny valley in the last year or so. And I think the things that have contributed to that are, one, better data. You’re seeing people invest a lot of money and brainpower and resources into adding more stuff into bigger data sets. We have whole groups that are taking every image they can get on the internet. Billions, billions of images from Pinterest and Amazon and Facebook. You have bigger data sets, so the A.I. is learning more. You also have better computing power, and those are the two ingredients to any good piece of A.I. So now you have A.I. that is not only trained to understand the world a little bit better, but it can now really quickly spit out a very finely detailed generated image.

Is there any way to know, when you look at a piece of A.I. art, what images it referenced to create what it’s doing? Or is it just so vast that you can’t kind of unspool it backward?

When you’re doing an image that’s totally generated out of nowhere, it’s taking bits of information from billions of images. It’s creating it in a much more sophisticated way so that it’s really hard to unspool.

Art generated by A.I. isn’t just a gee-whiz phenomenon, something that wins prizes, or even a fascinating subject for debate—it has valuable commercial uses, too. Some that are a little frightening if you’re, say, a graphic designer.

You’re already starting to see some of these images illustrating news articles, being used as logos for companies, being used in the form of stock art for small businesses and websites. Anything where somebody would’ve gone and paid an illustrator or graphic designer or artist to make something, they can now go to this A.I. and create something in a few seconds that is maybe not perfect, maybe would be beaten by a human in a head-to-head, but is good enough. From a commercial perspective, that’s scary, because we have an industry of people whose whole job is to create images, now running up against A.I.

And the A.I., again, in the last five years, the A.I. has gotten better and better. It’s still not perfect. I don’t think it’ll ever be perfect, whatever that looks like. It processes information in a different, maybe more literal, way than a human. I think human artists will still sort of have the upper hand in being able to imagine things a little more outside of the box. And yet, if you’re just looking for three people in a classroom or a pretty simple logo, you’re going to go to A.I. and you’re going to take potentially a job away from a freelancer whom you would’ve given it to 10 years ago.

I can see a use case here in marketing, in advertising. The A.I. doesn’t need health insurance, it doesn’t need paid vacation days, and I really do wonder about this idea that the A.I. could replace the jobs of visual artists. Do you think that is a legitimate fear, or is that overwrought at this moment?

I think it is a legitimate fear. When something can mirror your skill set, not 100 percent of the way, but enough of the way that it could replace you, that’s an issue. Do these A.I. creators have any kind of moral responsibility to not create it because it could put people out of jobs? I think that’s a debate, but I don’t think they see it that way. They see it like they’re just creating the new generation of digital camera, the new generation of Photoshop. But I think it is worth worrying about because even compared with cameras and Photoshop, the A.I. is a little bit more of the full package and it is so accessible and so hard to match in terms. It’s really going to be up to human artists to find some way to differentiate themselves from the A.I.

This is making me wonder about the humans underneath the data sets that the A.I. is trained on. The criticism is, of course, that these businesses are making money off thousands of artists’ work without their consent or knowledge and it undermines their work. Some people looked at the Stable Diffusion and they didn’t have access to its whole data set, but they found that Thomas Kinkade, the landscape painter, was the most referenced artist in the data set. Is the A.I. just piggybacking? And if it’s not Thomas Kinkade, if it’s someone who’s alive, are they piggybacking on that person’s work without that person getting paid?

Here’s a bit more on the topic of money and art in a September 19, 2022 article by John Herrman for New York Magazine. First, he starts with the literary arts, Note: Links have been removed,

Artificial-intelligence experts are excited about the progress of the past few years. You can tell! They’ve been telling reporters things like “Everything’s in bloom,” “Billions of lives will be affected,” and “I know a person when I talk to it — it doesn’t matter whether they have a brain made of meat in their head.”

We don’t have to take their word for it, though. Recently, AI-powered tools have been making themselves known directly to the public, flooding our social feeds with bizarre and shocking and often very funny machine-generated content. OpenAI’s GPT-3 took simple text prompts — to write a news article about AI or to imagine a rose ceremony from The Bachelor in Middle English — and produced convincing results.

Deepfakes graduated from a looming threat to something an enterprising teenager can put together for a TikTok, and chatbots are occasionally sending their creators into crisis.

More widespread, and probably most evocative of a creative artificial intelligence, is the new crop of image-creation tools, including DALL-E, Imagen, Craiyon, and Midjourney, which all do versions of the same thing. You ask them to render something. Then, with models trained on vast sets of images gathered from around the web and elsewhere, they try — “Bart Simpson in the style of Soviet statuary”; “goldendoodle megafauna in the streets of Chelsea”; “a spaghetti dinner in hell”; “a logo for a carpet-cleaning company, blue and red, round”; “the meaning of life.”

This flood of machine-generated media has already altered the discourse around AI for the better, probably, though it couldn’t have been much worse. In contrast with the glib intra-VC debate about avoiding human enslavement by a future superintelligence, discussions about image-generation technology have been driven by users and artists and focus on labor, intellectual property, AI bias, and the ethics of artistic borrowing and reproduction [emphasis mine]. Early controversies have cut to the chase: Is the guy who entered generated art into a fine-art contest in Colorado (and won!) an asshole? Artists and designers who already feel underappreciated or exploited in their industries — from concept artists in gaming and film and TV to freelance logo designers — are understandably concerned about automation. Some art communities and marketplaces have banned AI-generated images entirely.

Requests are effectively thrown into “a giant swirling whirlpool” of “10,000 graphics cards,” Holz [David Holz, Midjourney founder] said, after which users gradually watch them take shape, gaining sharpness but also changing form as Midjourney refines its work.

This hints at an externality beyond the worlds of art and design. “Almost all the money goes to paying for those machines,” Holz said. New users are given a small number of free image generations before they’re cut off and asked to pay; each request initiates a massive computational task, which means using a lot of electricity.

High compute costs [emphasis mine] — which are largely energy costs — are why other services have been cautious about adding new users. …

Another Midjourney user, Gila von Meissner, is a graphic designer and children’s-book author-illustrator from “the boondocks in north Germany.” Her agent is currently shopping around a book that combines generated images with her own art and characters. Like Pluckebaum [Brian Pluckebaum who works in automotive-semiconductor marketing and designs board games], she brought up the balance of power with publishers. “Picture books pay peanuts,” she said. “Most illustrators struggle financially.” Why not make the work easier and faster? “It’s my character, my edits on the AI backgrounds, my voice, and my story.” A process that took months now takes a week, she said. “Does that make it less original?”

User MoeHong, a graphic designer and typographer for the state of California, has been using Midjourney to make what he called generic illustrations (“backgrounds, people at work, kids at school, etc.”) for government websites, pamphlets, and literature: “I get some of the benefits of using custom art — not that we have a budget for commissions! — without the paying-an-artist part.” He said he has mostly replaced stock art, but he’s not entirely comfortable with the situation. “I have a number of friends who are commercial illustrators, and I’ve been very careful not to show them what I’ve made,” he said. He’s convinced that tools like this could eventually put people in his trade out of work. “But I’m already in my 50s,” he said, “and I hope I’ll be gone by the time that happens.”

Fan club

The last article I’m featuring here is a September 15, 2021 piece by Agnieszka Cichocka for DailyArt, which provides good, brief descriptions of algorithms, generative creative networks, machine learning, artificial neural networks, and more. She is an enthusiast (Note: Links have been removed),

I keep wondering if Leonardo da Vinci, who, in my opinion, was the most forward thinking artist of all time, would have ever imagined that art would one day be created by AI. He worked on numerous ideas and was constantly experimenting, and, although some were failures, he persistently tried new products, helping to move our world forward. Without such people, progress would not be possible. 

Machine Learning

As humans, we learn by acquiring knowledge through observations, senses, experiences, etc. This is similar to computers. Machine learning is a process in which a computer system learns how to perform a task better in two ways—either through exposure to environments that provide punishments and rewards (reinforcement learning) or by training with specific data sets (the system learns automatically and improves from previous experiences). Both methods help the systems improve their accuracy. Machines then use patterns and attempt to make an accurate analysis of things they have not seen before. To give an example, let’s say we feed the computer with thousands of photos of a dog. Consequently, it can learn what a dog looks like based on those. Later, even when faced with a picture it has never seen before, it can tell that the photo shows a dog.

If you want to see some creative machine learning experiments in art, check out ML x ART. This is a website with hundreds of artworks created using AI tools.

Some thoughts

As the saying goes “a picture is worth a thousand words” and, now, It seems that pictures will be made from words or so suggests the example of Jason M. Allen feeding prompts to the AI system Midjourney.

I suspect (as others have suggested) that in the end, artists who use AI systems will be absorbed into the art world in much the same way as artists who use photography, or are considered performance artists and/or conceptual artists, and/or use video have been absorbed. There will be some displacements and discomfort as the questions I opened this posting with (Who is an artist? What is an artist? Can everyone be an artist?) are passionately discussed and considered. Underlying many of these questions is the issue of money.

The impact on people’s livelihoods is cheering or concerning depending on how the AI system is being used. Herrman’s September 19, 2022 article highlights two examples that focus on graphic designers. Gila von Meissner, the illustrator and designer, who uses her own art to illustrate her children’s books in a faster, more cost effective way with an AI system and MoeHong, a graphic designer for the state of California, who uses an AI system to make ‘customized generic art’ for which the state government doesn’t have to pay.

So far, the focus has been on Midjourney and other AI agents that have been created by developers for use by visual artists and writers. What happens when the visual artist or the writer is the developer? A September 12, 2022 article by Brandon Scott Roye for Cool Hunting approaches the question (Note: Links have been removed),

Mario Klingemann and Sasha Stiles on Semi-Autonomous AI Artists

An artist and engineer at the forefront of generating AI artwork, Mario Klingemann and first-generation Kalmyk-American poet, artist and researcher Sasha Stiles both approach AI from a more human, personal angle. Creators of semi-autonomous systems, both Klingemann and Stiles are the minds behind Botto and Technelegy, respectively. They are both artists in their own right, but their creations are too. Within web3, the identity of the “artist” who creates with visuals and the “writer” who creates with words is enjoying a foundational shift and expansion. Many have fashioned themselves a new title as “engineer.”

Based on their primary identities as an artist and poet, Klingemann and Stiles face the conundrum of becoming engineers who design the tools, rather than artists responsible for the final piece. They now have the ability to remove themselves from influencing inputs and outputs.

If you have time, I suggest reading Roye’s September 12, 2022 article as it provides some very interesting ideas although I don’t necessarily agree with them, e.g., “They now have the ability to remove themselves from influencing inputs and outputs.” Anyone who’s following the ethics discussion around AI knows that biases are built into the algorithms whether we like it or not. As for artists and writers calling themselves ‘engineers’, they may get a little resistance from the engineering community.

As users of open source software, Klingemann and Stiles should not have to worry too much about intellectual property. However, it seems copyright for the actual works and patents for the software could raise some interesting issues especially since money is involved.

In a March 10, 2022 article by Shraddha Nair for Stir World, Klingemann claims to have made over $1M from auctions of Botto’s artworks. it’s not clear to me where Botto obtains its library of images for future use (which may signal a potential problem); Stiles’ Technelegy creates poems from prompts using its library of her poems. (For the curious, I have an August 30, 2022 post “Should AI algorithms get patents for their inventions and is anyone talking about copyright for texts written by AI algorithms?” which explores some of the issues around patents.)

Who gets the patent and/or the copyright? Assuming you and I are employing machine learning to train our AI agents separately, could there be an argument that if my version of the AI is different than yours and proves more popular with other content creators/ artists that I should own/share the patent to the software and rights to whatever the software produces?

Getting back to Herrman’s comment about high compute costs and energy, we seem to have an insatiable appetite for energy and that is not only a high cost financially but also environmentally.

Botto exhibition

Here’s more about Klingemann’s artist exhibition by Botto (from an October 6, 2022 announcement received via email),

Mario Klingemann is a pioneering figurehead in the field of AI art,
working deep in the field of Machine Learning. Governed by a community
of 5,000 people, Klingemann developed Botto around an idea of creating
an autonomous entity that is able to be creative and co-creative.
Inspired by Goethe’s artificial man in Faust, Botto is a genderless AI
entity that is guided by an international community and art historical
trends. Botto creates 350 art pieces per week that are presented to its
community. Members of the community give feedback on these art fragments
by voting, expressing their individual preferences on what is
aesthetically pleasing to them. Then collectively the votes are used as
feedback for Botto’s generative algorithm, dictating what direction
Botto should take in its next series of art pieces.

The creative capacity of its algorithm is far beyond the capacities of
an individual to combine and find relationships within all the
information available to the AI. Botto faces similar issues as a human
artist, and it is programmed to self-reflect and ask, “I’ve created
this type of work before. What can I show them that’s different this
week?”

Once a week, Botto auctions the art fragment with the most votes on
SuperRare. All proceeds from the auction go back to the community. The
AI artist auctioned its first three pieces, Asymmetrical Liberation,
Scene Precede, and Trickery Contagion for more than $900,000 dollars,
the most successful AI artist premiere. Today, Botto has produced
upwards of 22 artworks and current sales have generated over $2 million
in total
[emphasis mine].

From March 2022 when Botto had made $1M to October 2022 where it’s made over $2M. It seems Botto is a very financially successful artist.

Botto: A Whole Year of Co-Creation

This exhibition (October 26 – 30, 2022) is being held in London, England at this location:

The Department Store, Brixton 248 Ferndale Road London SW9 8FR United Kingdom

Enjoy!

Quantum memristors

This March 24, 2022 news item on Nanowerk announcing work on a quantum memristor seems to have had a rough translation from German to English,

In recent years, artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world’s largest supercomputer.

Physicists at the University of Vienna have now demonstrated a new device, called quantum memristor, which may allow to combine these two worlds, thus unlocking unprecedented capabilities. The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy, has been realized on an integrated quantum processor operating on single photons.

Caption: Abstract representation of a neural network which is made of photons and has memory capability potentially related to artificial intelligence. Credit: © Equinox Graphics, University of Vienna

A March 24, 2022 University of Vienna (Universität Wien) press release (also on EurekAlert), which originated the news item, explains why this work has an impact on artificial intelligence,

At the heart of all artificial intelligence applications are mathematical models called neural networks. These models are inspired by the biological structure of the human brain, made of interconnected nodes. Just like our brain learns by constantly rearranging the connections between neurons, neural networks can be mathematically trained by tuning their internal structure until they become capable of human-level tasks: recognizing our face, interpreting medical images for diagnosis, even driving our cars. Having integrated devices capable of performing the computations involved in neural networks quickly and efficiently has thus become a major research focus, both academic and industrial.

One of the major game changers in the field was the discovery of the memristor, made in 2008. This device changes its resistance depending on a memory of the past current, hence the name memory-resistor, or memristor. Immediately after its discovery, scientists realized that (among many other applications) the peculiar behavior of memristors was surprisingly similar to that of neural synapses. The memristor has thus become a fundamental building block of neuromorphic architectures.

A group of experimental physicists from the University of Vienna, the National Research Council (CNR) and the Politecnico di Milano led by Prof. Philip Walther and Dr. Roberto Osellame, have now demonstrated that it is possible to engineer a device that has the same behavior as a memristor, while acting on quantum states and being able to encode and transmit quantum information. In other words, a quantum memristor. Realizing such device is challenging because the dynamics of a memristor tends to contradict the typical quantum behavior. 

By using single photons, i.e. single quantum particles of lights, and exploiting their unique ability to propagate simultaneously in a superposition of two or more paths, the physicists have overcome the challenge. In their experiment, single photons propagate along waveguides laser-written on a glass substrate and are guided on a superposition of several paths. One of these paths is used to measure the flux of photons going through the device and this quantity, through a complex electronic feedback scheme, modulates the transmission on the other output, thus achieving the desired memristive behavior. Besides demonstrating the quantum memristor, the researchers have provided simulations showing that optical networks with quantum memristor can be used to learn on both classical and quantum tasks, hinting at the fact that the quantum memristor may be the missing link between artificial intelligence and quantum computing.

“Unlocking the full potential of quantum resources within artificial intelligence is one of the greatest challenges of the current research in quantum physics and computer science”, says Michele Spagnolo, who is first author of the publication in the journal “Nature Photonics”. The group of Philip Walther of the University of Vienna has also recently demonstrated that robots can learn faster when using quantum resources and borrowing schemes from quantum computation. This new achievement represents one more step towards a future where quantum artificial intelligence become reality.

Here’s a link to and a citation for the paper,

Experimental photonic quantum memristor by Michele Spagnolo, Joshua Morris, Simone Piacentini, Michael Antesberger, Francesco Massa, Andrea Crespi, Francesco Ceccarelli, Roberto Osellame & Philip Walther. Nature Photonics volume 16, pages 318–323 (2022) DOI: https://doi.org/10.1038/s41566-022-00973-5 Published 24 March 2022 Issue Date April 2022

This paper is open access.

Age of AI and Big Data – Impact on Justice, Human Rights and Privacy Zoom event on September 28, 2022 at 12 – 1:30 pm EDT

The Canadian Science Policy Centre (CSPC) in a September 15, 2022 announcement (received via email) announced an event (Age of AI and Big Data – Impact on Justice, Human Rights and Privacy) centered on some of the latest government doings on artificial intelligence and privacy (Bill C-27),

In an increasingly connected world, we share a large amount of our data in our daily lives without our knowledge while browsing online, traveling, shopping, etc. More and more companies are collecting our data and using it to create algorithms or AI. The use of our data against us is becoming more and more common. The algorithms used may often be discriminatory against racial minorities and marginalized people.

As technology moves at a high pace, we have started to incorporate many of these technologies into our daily lives without understanding its consequences. These technologies have enormous impacts on our very own identity and collectively on civil society and democracy. 

Recently, the Canadian Government introduced the Artificial Intelligence and Data Act (AIDA) and Bill C-27 [which includes three acts in total] in parliament regulating the use of AI in our society. In this panel, we will discuss how our AI and Big data is affecting us and its impact on society, and how the new regulations affect us. 

Date: Sep 28 Time: 12:00 pm – 1:30 pm EDT Event Category: Virtual Session

Register Here

For some reason, there was no information about the moderator and panelists, other than their names, titles, and affiliations. Here’s a bit more:

Moderator: Yuan Stevens (from her eponymous website’s About page), Note: Links have been removed,

Yuan (“You-anne”) Stevens (she/they) is a legal and policy expert focused on sociotechnical security and human rights.

She works towards a world where powerful actors—and the systems they build—are held accountable to the public, especially when it comes to marginalized communities. 

She brings years of international experience to her role at the Leadership Lab at Toronto Metropolitan University [formerly Ryerson University], having examined the impacts of technology on vulnerable populations in Canada, the US and Germany. 

Committed to publicly accessible legal and technical knowledge, Yuan has written for popular media outlets such as the Toronto Star and Ottawa Citizen and has been quoted in news stories by the New York Times, the CBC and the Globe & Mail.

Yuan is a research fellow at the Centre for Law, Technology and Society at the University of Ottawa and a research affiliate at Data & Society Research Institute. She previously worked at Harvard University’s Berkman Klein Center for Internet & Society during her studies in law at McGill University.

She has been conducting research on artificial intelligence since 2017 and is currently exploring sociotechnical security as an LL.M candidate at University of Ottawa’s Faculty of Law working under Florian Martin-Bariteau.

Panelist: Brenda McPhail (from her Centre for International Governance Innovation profile page),

Brenda McPhail is the director of the Canadian Civil Liberties Association’s Privacy, Surveillance and Technology Project. Her recent work includes guiding the Canadian Civil Liberties Association’s interventions in key court cases that raise privacy issues, most recently at the Supreme Court of Canada in R v. Marakah and R v. Jones, which focused on privacy rights in sent text messages; research into surveillance of dissent, government information sharing, digital surveillance capabilities and privacy in relation to emergent technologies; and developing resources and presentations to drive public awareness about the importance of privacy as a social good.

Panelist: Nidhi Hegde (from her University of Alberta profile page),

My research has spanned many areas such as resource allocation in networking, smart grids, social information networks, machine learning. Broadly, my interest lies in gaining a fundamental understanding of a given system and the design of robust algorithms.

More recently my research focus has been in privacy in machine learning. I’m interested in understanding how robust machine learning methods are to perturbation, and privacy and fairness constraints, with the goal of designing practical algorithms that achieve privacy and fairness.

Bio

Before joining the University of Alberta, I spent many years in industry research labs. Most recently, I was a Research team lead at Borealis AI (a research institute at Royal Bank of Canada), where my team worked on privacy-preserving methods for machine learning models and other applied problems for RBC. Prior to that, I spent many years in research labs in Europe working on a variety of interesting and impactful problems. I was a researcher at Bell Labs, Nokia, in France from January 2015 to March 2018, where I led a new team focussed on Maths and Algorithms for Machine Learning in Networks and Systems, in the Maths and Algorithms group of Bell Labs. I also spent a few years at the Technicolor Paris Research Lab working on social network analysis, smart grids, and privacy in recommendations.

Panelist: Benjamin Faveri (from his LinkedIn page),

About

Benjamin Faveri is a Research and Policy Analyst at the Responsible AI Institute (RAII) [headquarted in Austin, Texas]. Currently, he is developing their Responsible AI Certification Program and leading it through Canada’s national accreditation process. Over the last several years, he has worked on numerous certification program-related research projects such as fishery economics and certification programs, police body-worn camera policy certification, and emerging AI certifications and assurance systems. Before his work at RAII, Benjamin completed a Master of Public Policy and Administration at Carleton University, where he was a Canada Graduate Scholar, Ontario Graduate Scholar, Social Innovation Fellow, and Visiting Scholar at UC Davis School of Law. He holds undergraduate degrees in criminology and psychology, finishing both with first class standing. Outside of work, Benjamin reads about how and why certification and private governance have been applied across various industries.

Panelist: Ori Freiman (from his eponymous website’s About page)

I research at the forefront of technological innovation. This website documents some of my academic activities.

My formal background is in Analytic Philosophy, Library and Information Science, and Science & Technology Studies. Until September 22′ [September 2022], I was a Post-Doctoral Fellow at the Ethics of AI Lab, at the University of Toronto’s Centre for Ethics. Before joining the Centre, I submitted my dissertation, about trust in technology, to The Graduate Program in Science, Technology and Society at Bar-Ilan University.

I have also found a number of overviews and bits of commentary about the Canadian federal government’s proposed Bill C-27, which I think of as an omnibus bill as it includes three proposed Acts.

The lawyers are excited but I’m starting with the Responsible AI Institute’s (RAII) response first as one of the panelists (Benjamin Faveri) works for them and it’s a view from a closely neighbouring country, from a June 22, 2022 RAII news release, Note: Links have been removed,

Business Implications of Canada’s Draft AI and Data Act

On June 16 [2022], the Government of Canada introduced the Artificial Intelligence and Data Act (AIDA), as part of the broader Digital Charter Implementation Act 2022 (Bill C-27). Shortly thereafter, it also launched the second phase of the Pan-Canadian Artificial Intelligence Strategy.

Both RAII’s Certification Program, which is currently under review by the Standards Council of Canada, and the proposed AIDA legislation adopt the same approach of gauging an AI system’s risk level in context; identifying, assessing, and mitigating risks both pre-deployment and on an ongoing basis; and pursuing objectives such as safety, fairness, consumer protection, and plain-language notification and explanation.

Businesses should monitor the progress of Bill C-27 and align their AI governance processes, policies, and controls to its requirements. Businesses participating in RAII’s Certification Program will already be aware of requirements, such as internal Algorithmic Impact Assessments to gauge risk level and Responsible AI Management Plans for each AI system, which include system documentation, mitigation measures, monitoring requirements, and internal approvals.

The AIDA draft is focused on the impact of any “high-impact system”. Companies would need to assess whether their AI systems are high-impact; identify, assess, and mitigate potential harms and biases flowing from high-impact systems; and “publish on a publicly available website a plain-language description of the system” if making a high-impact system available for use. The government elaborated in a press briefing that it will describe in future regulations the classes of AI systems that may have high impact.

The AIDA draft also outlines clear criminal penalties for entities which, in their AI efforts, possess or use unlawfully obtained personal information or knowingly make available for use an AI system that causes serious harm or defrauds the public and causes substantial economic loss to an individual.

If enacted, AIDA would establish the Office of the AI and Data Commissioner, to support Canada’s Minister of Innovation, Science and Economic Development, with powers to monitor company compliance with the AIDA, to order independent audits of companies’ AI activities, and to register compliance orders with courts. The Commissioner would also help the Minister ensure that standards for AI systems are aligned with international standards.

Apart from being aligned with the approach and requirements of Canada’s proposed AIDA legislation, RAII is also playing a key role in the Standards Council of Canada’s AI  accreditation pilot. The second phase of the Pan-Canadian includes funding for the Standards Council of Canada to “advance the development and adoption of standards and a conformity assessment program related to AI/”

The AIDA’s introduction shows that while Canada is serious about governing AI systems, its approach to AI governance is flexible and designed to evolve as the landscape changes.

Charles Mandel’s June 16, 2022 article for Betakit (Canadian Startup News and Tech Innovation) provides an overview of the government’s overall approach to data privacy, AI, and more,

The federal Liberal government has taken another crack at legislating privacy with the introduction of Bill C-27 in the House of Commons.

Among the bill’s highlights are new protections for minors as well as Canada’s first law regulating the development and deployment of high-impact AI systems.

“It [Bill C-27] will address broader concerns that have been expressed since the tabling of a previous proposal, which did not become law,” a government official told a media technical briefing on the proposed legislation.

François-Philippe Champagne, the Minister of Innovation, Science and Industry, together with David Lametti, the Minister of Justice and Attorney General of Canada, introduced the Digital Charter Implementation Act, 2022. The ministers said Bill C-27 will significantly strengthen Canada’s private sector privacy law, create new rules for the responsible development and use of artificial intelligence (AI), and continue to put in place Canada’s Digital Charter.

The Digital Charter Implementation Act includes three proposed acts: the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act, and the Artificial Intelligence and Data Act (AIDA)- all of which have implications for Canadian businesses.

Bill C-27 follows an attempt by the Liberals to introduce Bill C-11 in 2020. The latter was the federal government’s attempt to reform privacy laws in Canada, but it failed to gain passage in Parliament after the then-federal privacy commissioner criticized the bill.

The proposed Artificial Intelligence and Data Act is meant to protect Canadians by ensuring high-impact AI systems are developed and deployed in a way that identifies, assesses and mitigates the risks of harm and bias.

For businesses developing or implementing AI this means that the act will outline criminal prohibitions and penalties regarding the use of data obtained unlawfully for AI development or where the reckless deployment of AI poses serious harm and where there is fraudulent intent to cause substantial economic loss through its deployment.

..

An AI and data commissioner will support the minister of innovation, science, and industry in ensuring companies comply with the act. The commissioner will be responsible for monitoring company compliance, ordering third-party audits, and sharing information with other regulators and enforcers as appropriate.

The commissioner would also be expected to outline clear criminal prohibitions and penalties regarding the use of data obtained unlawfully for AI development or where the reckless deployment of AI poses serious harm and where there is fraudulent intent to cause substantial economic loss through its deployment.

Canada already collaborates on AI standards to some extent with a number of countries. Canada, France, and 13 other countries launched an international AI partnership to guide policy development and “responsible adoption” in 2020.

The federal government also has the Pan-Canadian Artificial Intelligence Strategy for which it committed an additional $443.8 million over 10 years in Budget 2021. Ahead of the 2022 budget, Trudeau [Canadian Prime Minister Justin Trudeau] had laid out an extensive list of priorities for the innovation sector, including tasking Champagne with launching or expanding national strategy on AI, among other things.

Within the AI community, companies and groups have been looking at AI ethics for some time. Scotiabank donated $750,000 in funding to the University of Ottawa in 2020 to launch a new initiative to identify solutions to issues related to ethical AI and technology development. And Richard Zemel, co-founder of the Vector Institute [formed as part of the Pan-Canadian Artificial Intelligence Strategy], joined Integrate.AI as an advisor in 2018 to help the startup explore privacy and fairness in AI.

When it comes to the Consumer Privacy Protection Act, the Liberals said the proposed act responds to feedback received on the proposed legislation, and is meant to ensure that the privacy of Canadians will be protected, and that businesses can benefit from clear rules as technology continues to evolve.

“A reformed privacy law will establish special status for the information of minors so that they receive heightened protection under the new law,” a federal government spokesperson told the technical briefing.

..

The act is meant to provide greater controls over Canadians’ personal information, including how it is handled by organizations as well as giving Canadians the freedom to move their information from one organization to another in a secure manner.

The act puts the onus on organizations to develop and maintain a privacy management program that includes the policies, practices and procedures put in place to fulfill obligations under the act. That includes the protection of personal information, how requests for information and complaints are received and dealt with, and the development of materials to explain an organization’s policies and procedures.

The bill also ensures that Canadians can request that their information be deleted from organizations.

The bill provides the privacy commissioner of Canada with broad powers, including the ability to order a company to stop collecting data or using personal information. The commissioner will be able to levy significant fines for non-compliant organizations—with fines of up to five percent of global revenue or $25 million, whichever is greater, for the most serious offences.

The proposed Personal Information and Data Protection Tribunal Act will create a new tribunal to enforce the Consumer Privacy Protection Act.

Although the Liberal government said it engaged with stakeholders for Bill C-27, the Council of Canadian Innovators (CCI) expressed reservations about the process. Nick Schiavo, CCI’s director of federal affairs, said it had concerns over the last version of privacy legislation, and had hoped to present those concerns when the bill was studied at committee, but the previous bill died before that could happen.

Now the lawyers. Simon Hodgett, Kuljit Bhogal, and Sam Ip have written a June 27, 2022 overview, which highlights the key features from the perspective of Osler, a leading business law firm practising internationally from offices across Canada and in New York.

Maya Medeiros and Jesse Beatson authored a June 23, 2022 article for Norton Rose Fulbright, a global law firm, which notes a few ‘weak’ spots in the proposed legislation,

… While the AIDA is directed to “high-impact” systems and prohibits “material harm,” these and other key terms are not yet defined. Further, the quantum of administrative penalties will be fixed only upon the issuance of regulations. 

Moreover, the AIDA sets out publication requirements but it is unclear if there will be a public register of high-impact AI systems and what level of technical detail about the AI systems will be available to the public. More clarity should come through Bill C-27’s second and third readings in the House of Commons, and subsequent regulations if the bill passes.

The AIDA may have extraterritorial application if components of global AI systems are used, developed, designed or managed in Canada. The European Union recently introduced its Artificial Intelligence Act, which also has some extraterritorial application. Other countries will likely follow. Multi-national companies should develop a coordinated global compliance program.

I have two podcasts from Michael Geist, a lawyer and Canada Research Chair in Internet and E-Commerce Law at the University of Ottawa.

  • June 26, 2022: The Law Bytes Podcast, Episode 132: Ryan Black on the Government’s Latest Attempt at Privacy Law Reform “The privacy reform bill that is really three bills in one: a reform of PIPEDA, a bill to create a new privacy tribunal, and an artificial intelligence regulation bill. What’s in the bill from a privacy perspective and what’s changed? Is this bill any likelier to become law than an earlier bill that failed to even advance to committee hearings? To help sort through the privacy aspects of Bill C-27, Ryan Black, a Vancouver-based partner with the law firm DLA Piper (Canada) …” (about 45 mins.)
  • August 15, 2022: The Law Bytes Podcast, Episode 139: Florian Martin-Bariteau on the Artificial Intelligence and Data Act “Critics argue that regulations are long overdue, but have expressed concern about how much of the substance is left for regulations that are still to be developed. Florian Martin-Bariteau is a friend and colleague at the University of Ottawa, where he holds the University Research Chair in Technology and Society and serves as director of the Centre for Law, Technology and Society. He is currently a fellow at the Harvard’s Berkman Klein Center for Internet and Society …” (about 38 mins.)