Tag Archives: Erik Brynjolfsson

Artificial emotional intelligence detection

Sabotage was not my first thought on reading about artificial emotional intelligence so this February 11, 2021 Incheon National University press release (also on EurekAlert) is educational in an unexpected way (Note: A link has been removed),

With the advent of 5G communication technology and its integration with AI, we are looking at the dawn of a new era in which people, machines, objects, and devices are connected like never before. This smart era will be characterized by smart facilities and services such as self-driving cars, smart UAVs [unmanned aerial vehicle], and intelligent healthcare. This will be the aftermath of a technological revolution.

But the flip side of such technological revolution is that AI [artificial intelligence] itself can be used to attack or threaten the security of 5G-enabled systems which, in turn, can greatly compromise their reliability. It is, therefore, imperative to investigate such potential security threats and explore countermeasures before a smart world is realized.

In a recent study published in IEEE Network, a team of researchers led by Prof. Hyunbum Kim from Incheon National University, Korea, address such issues in relation to an AI-based, 5G-integrated virtual emotion recognition system called 5G-I-VEmoSYS, which detects human emotions using wireless signals and body movement. “Emotions are a critical characteristic of human beings and separates humans from machines, defining daily human activity. However, some emotions can also disrupt the normal functioning of a society and put people’s lives in danger, such as those of an unstable driver. Emotion detection technology thus has great potential for recognizing any disruptive emotion and in tandem with 5G and beyond-5G communication, warning others of potential dangers,” explains Prof. Kim. “For instance, in the case of the unstable driver, the AI enabled driver system of the car can inform the nearest network towers, from where nearby pedestrians can be informed via their personal smart devices.”

The virtual emotion system developed by Prof. Kim’s team, 5G-I-VEmoSYS, can recognize at least five kinds of emotion (joy, pleasure, a neutral state, sadness, and anger) and is composed of three subsystems dealing with the detection, flow, and mapping of human emotions. The system concerned with detection is called Artificial Intelligence-Virtual Emotion Barrier, or AI-VEmoBAR, which relies on the reflection of wireless signals from a human subject to detect emotions. This emotion information is then handled by the system concerned with flow, called Artificial Intelligence-Virtual Emotion Flow, or AI-VEmoFLOW, which enables the flow of specific emotion information at a specific time to a specific area. Finally, the Artificial Intelligence-Virtual Emotion Map, or AI-VEmoMAP, utilizes a large amount of this virtual emotion data to create a virtual emotion map that can be utilized for threat detection and crime prevention.

A notable advantage of 5G-I-VEmoSYS is that it allows emotion detection without revealing the face or other private parts of the subjects, thereby protecting the privacy of citizens in public areas. Moreover, in private areas, it gives the user the choice to remain anonymous while providing information to the system. Furthermore, when a serious emotion, such as anger or fear, is detected in a public area, the information is rapidly conveyed to the nearest police department or relevant entities who can then take steps to prevent any potential crime or terrorism threats.

However, the system suffers from serious security issues such as the possibility of illegal signal tampering, abuse of anonymity, and hacking-related cyber-security threats. Further, the danger of sending false alarms to authorities remains.

While these concerns do put the system’s reliability at stake, Prof. Kim’s team are confident that they can be countered with further research. “This is only an initial study. In the future, we need to achieve rigorous information integrity and accordingly devise robust AI-based algorithms that can detect compromised or malfunctioning devices and offer protection against potential system hacks,” explains Prof. Kim, “Only then will it enable people to have safer and more convenient lives in the advanced smart cities of the future.”

Intriguing, yes? The researchers have used this image to illustrate their work,

Caption: With 5G communication technology and new AI-based systems such as emotion recognition systems, smart cities are all set to become a reality; but these systems need to be honed and security issues need to be ironed out before the smart reality can be realized. Credit: macrovector on Freepik

Before getting to the link and citation for the paper, I have a March 8, 2019 article by Meredith Somers for MIT (Massachusetts Institute of Technology) Sloan School of Management’s Ideas Made to Matter publication (Note Links have been removed),

What did you think of the last commercial you watched? Was it funny? Confusing? Would you buy the product? You might not remember or know for certain how you felt, but increasingly, machines do. New artificial intelligence technologies are learning and recognizing human emotions, and using that knowledge to improve everything from marketing campaigns to health care.

These technologies are referred to as “emotion AI.” Emotion AI is a subset of artificial intelligence (the broad term for machines replicating the way humans think) that measures, understands, simulates, and reacts to human emotions. It’s also known as affective computing, or artificial emotional intelligence. The field dates back to at least 1995, when MIT Media lab professor Rosalind Picard published “Affective Computing.”

Javier Hernandez, a research scientist with the Affective Computing Group at the MIT Media Lab, explains emotion AI as a tool that allows for a much more natural interaction between humans and machines.“Think of the way you interact with other human beings; you look at their faces, you look at their body, and you change your interaction accordingly,” Hernandez said. “How can [a machine] effectively communicate information if it doesn’t know your emotional state, if it doesn’t know how you’re feeling, it doesn’t know how you’re going to respond to specific content?”

While humans might currently have the upper hand on reading emotions, machines are gaining ground using their own strengths. Machines are very good at analyzing large amounts of data, explained MIT Sloan professor Erik Brynjolfsson. They can listen to voice inflections and start to recognize when those inflections correlate with stress or anger. Machines can analyze images and pick up subtleties in micro-expressions on humans’ faces that might happen even too fast for a person to recognize.

“We have a lot of neurons in our brain for social interactions. We’re born with some of those skills, and then we learn more. It makes sense to use technology to connect to our social brains, not just our analytical brains.” Brynjolfsson said. “Just like we can understand speech and machines can communicate in speech, we also understand and communicate with humor and other kinds of emotions. And machines that can speak that language — the language of emotions — are going to have better, more effective interactions with us. It’s great that we’ve made some progress; it’s just something that wasn’t an option 20 or 30 years ago, and now it’s on the table.”

Somers describes current uses of emotion AI (I’ve selected two from her list; Note: A link has been removed),

Call centers —Technology from Cogito, a company co-founded in 2007 by MIT Sloan alumni, helps call center agents identify the moods of customers on the phone and adjust how they handle the conversation in real time. Cogito’s voice-analytics software is based on years of human behavior research to identify voice patterns.

Mental health —  In December 2018 Cogito launched a spinoff called CompanionMx, and an accompanying mental health monitoring app. The Companion app listens to someone speaking into their phone, and analyzes the speaker’s voice and phone use for signs of anxiety and mood changes.

The app improves users’ self-awareness, and can increase coping skills including steps for stress reduction. The company has worked with the Department of Veterans Affairs, the Massachusetts General Hospital, and Brigham & Women’s Hospital in Boston.

Somers’ March 8, 2019 article was an eye-opener.

Getting back to the Korean research, here’s a link to and a citation for the paper,

Research Challenges and Security Threats to AI-Driven 5G Virtual Emotion Applications Using Autonomous Vehicles, Drones, and Smart Devices by Hyunbum Kim; Jalel Ben-Othman; Lynda Mokdad; Junggab Son; Chunguo Li. IEEE Network Volume: 34 Issue: 6 November/December 2020 Page(s): 288 – 294 DOI: 10.1109/MNET.011.2000245 Date of Publication (online): 12 October 2020

This paper is behind a paywall.

Tracking artificial intelligence

Researchers at Stanford University have developed an index for measuring (tracking) the progress made by artificial intelligence (AI) according to a January 9, 2018 news item on phys.org (Note: Links have been removed),

Since the term “artificial intelligence” (AI) was first used in print in 1956, the one-time science fiction fantasy has progressed to the very real prospect of driverless cars, smartphones that recognize complex spoken commands and computers that see.

In an effort to track the progress of this emerging field, a Stanford-led group of leading AI thinkers called the AI100 has launched an index that will provide a comprehensive baseline on the state of artificial intelligence and measure technological progress in the same way the gross domestic product and the S&P 500 index track the U.S. economy and the broader stock market.

For anyone curious about the AI100 initiative, I have a description of it in my Sept. 27, 2016 post highlighting the group’s first report or you can keep on reading.

Getting back to the matter at hand, a December 21, 2017 Stanford University press release by Andrew Myers, which originated the news item, provides more detail about the AI index,

“The AI100 effort realized that in order to supplement its regular review of AI, a more continuous set of collected metrics would be incredibly useful,” said Russ Altman, a professor of bioengineering and the faculty director of AI100. “We were very happy to seed the AI Index, which will inform the AI100 as we move forward.”

The AI100 was set in motion three years ago when Eric Horvitz, a Stanford alumnus and former president of the Association for the Advancement of Artificial Intelligence, worked with his wife, Mary Horvitz, to define and endow the long-term study. Its first report, released in the fall of 2016, sought to anticipate the likely effects of AI in an urban environment in the year 2030.

Among the key findings in the new index are a dramatic increase in AI startups and investment as well as significant improvements in the technology’s ability to mimic human performance.

Baseline metrics

The AI Index tracks and measures at least 18 independent vectors in academia, industry, open-source software and public interest, plus technical assessments of progress toward what the authors call “human-level performance” in areas such as speech recognition, question-answering and computer vision – algorithms that can identify objects and activities in 2D images. Specific metrics in the index include evaluations of academic papers published, course enrollment, AI-related startups, job openings, search-term frequency and media mentions, among others.

“In many ways, we are flying blind in our discussions about artificial intelligence and lack the data we need to credibly evaluate activity,” said Yoav Shoham, professor emeritus of computer science.

“The goal of the AI Index is to provide a fact-based measuring stick against which we can chart progress and fuel a deeper conversation about the future of the field,” Shoham said.

Shoham conceived of the index and assembled a steering committee including Ray Perrault from SRI International, Erik Brynjolfsson of the Massachusetts Institute of Technology and Jack Clark from OpenAI. The committee subsequently hired Calvin LeGassick as project manager.

“The AI Index will succeed only if it becomes a community effort,” Shoham said.

Although the authors say the AI Index is the first index to track either scientific or technological progress, there are many other non-financial indexes that provide valuable insight into equally hard-to-quantify fields. Examples include the Social Progress Index, the Middle East peace index and the Bangladesh empowerment index, which measure factors as wide-ranging as nutrition, sanitation, workload, leisure time, public sentiment and even public speaking opportunities.

Intriguing findings

Among the findings of this inaugural index is that the number of active AI startups has increased 14-fold since 2000. Venture capital investment has increased six times in the same period. In academia, publishing in AI has increased a similarly impressive nine times in the last 20 years while course enrollment has soared. Enrollment in the introductory AI-related machine learning course at Stanford, for instance, has grown 45-fold in the last 30 years.

In technical metrics, image and speech recognition are both approaching, if not surpassing, human-level performance. The authors noted that AI systems have excelled in such real-world applications as object detection, the ability to understand and answer questions and classification of photographic images of skin cancer cells

Shoham noted that the report is still very U.S.-centric and will need a greater international presence as well as a greater diversity of voices. He said he also sees opportunities to fold in government and corporate investment in addition to the venture capital funds that are currently included.

In terms of human-level performance, the AI Index suggests that in some ways AI has already arrived. This is true in game-playing applications including chess, the Jeopardy! game show and, most recently, the game of Go. Nonetheless, the authors note that computers continue to lag considerably in the ability to generalize specific information into deeper meaning.

“AI has made truly amazing strides in the past decade,” Shoham said, “but computers still can’t exhibit the common sense or the general intelligence of even a 5-year-old.”

The AI Index was made possible by funding from AI100, Google, Microsoft and Toutiao. Data supporting the various metrics were provided by Elsevier, TrendKite, Indeed.com, Monster.com, the Google Trends Team, the Google Brain Team, Sand Hill Econometrics, VentureSource, Crunchbase, Electronic Frontier Foundation, EuroMatrix, Geoff Sutcliffe, Kevin Leyton-Brown and Holger Hoose.

You can find the AI Index here. They’re featuring their 2017 report but you can also find data (on the menu bar on the upper right side of your screen), along with a few provisos. I was curious as to whether any AI had been used to analyze the data and/or write the report. A very cursory look at the 2017 report did not answer that question. I’m fascinated by the failure to address what I think is an obvious question. It suggests that even very, very bright people can become blind and I suspect that’s why the group seems quite eager to get others involved, from the 2017 AI Index Report,

As the report’s limitations illustrate, the AI Index will always paint a partial picture. For this reason, we include subjective commentary from a cross-section of AI experts. This Expert Forum helps animate the story behind the data in the report and adds interpretation the report lacks.

Finally, where the experts’ dialogue ends, your opportunity to Get Involved begins [emphasis mine]. We will need the feedback and participation of a larger community to address the issues identified in this report, uncover issues we have omitted, and build a productive process for tracking activity and progress in Artificial Intelligence. (p. 8)

Unfortunately, it’s not clear how one becomes involved. Is there a forum or do you get in touch with one of the team leaders?

I wish them good luck with their project and imagine that these minor hiccups will be dealt with in near term.

How might artificial intelligence affect urban life in 2030? A study

Peering into the future is always a chancy business as anyone who’s seen those film shorts from the 1950’s and 60’s which speculate exuberantly as to what the future will bring knows.

A sober approach (appropriate to our times) has been taken in a study about the impact that artificial intelligence might have by 2030. From a Sept. 1, 2016 Stanford University news release (also on EurekAlert) by Tom Abate (Note: Links have been removed),

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city – in areas as diverse as transportation, health care and education ­– and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies.

Titled “Artificial Intelligence and Life in 2030,” this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines.

“We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life,” said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. “But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford. AI100 formed a standing committee of scientists and charged this body with commissioning periodic reports on different aspects of AI over the ensuing century.

“This process will be a marathon, not a sprint, but today we’ve made a good start,” said Russ Altman, a professor of bioengineering and the Stanford faculty director of AI100. “Stanford is excited to host this process of introspection. This work makes practical contribution to the public debate on the roles and implications of artificial intelligence.”

The AI100 standing committee first met in 2015, led by chairwoman and Harvard computer scientist Barbara Grosz. It sought to convene a panel of scientists with diverse professional and personal backgrounds and enlist their expertise to assess the technological, economic and policy implications of potential AI applications in a societally relevant setting.

“AI technologies can be reliable and broadly beneficial,” Grosz said. “Being transparent about their design and deployment challenges will build trust and avert unjustified fear and suspicion.”

The report investigates eight domains of human activity in which AI technologies are beginning to affect urban life in ways that will become increasingly pervasive and profound by 2030.

The 28,000-word report includes a glossary to help nontechnical readers understand how AI applications such as computer vision might help screen tissue samples for cancers or how natural language processing will allow computerized systems to grasp not simply the literal definitions, but the connotations and intent, behind words.

The report is broken into eight sections focusing on applications of AI. Five examine application arenas such as transportation where there is already buzz about self-driving cars. Three other sections treat technological impacts, like the section on employment and workplace trends which touches on the likelihood of rapid changes in jobs and incomes.

“It is not too soon for social debate on how the fruits of an AI-dominated economy should be shared,” the researchers write in the report, noting also the need for public discourse.

“Currently in the United States, at least sixteen separate agencies govern sectors of the economy related to AI technologies,” the researchers write, highlighting issues raised by AI applications: “Who is responsible when a self-driven car crashes or an intelligent medical device fails? How can AI applications be prevented from [being used for] racial discrimination or financial cheating?”

The eight sections discuss:

Transportation: Autonomous cars, trucks and, possibly, aerial delivery vehicles may alter how we commute, work and shop and create new patterns of life and leisure in cities.

Home/service robots: Like the robotic vacuum cleaners already in some homes, specialized robots will clean and provide security in live/work spaces that will be equipped with sensors and remote controls.

Health care: Devices to monitor personal health and robot-assisted surgery are hints of things to come if AI is developed in ways that gain the trust of doctors, nurses, patients and regulators.

Education: Interactive tutoring systems already help students learn languages, math and other skills. More is possible if technologies like natural language processing platforms develop to augment instruction by humans.

Entertainment: The conjunction of content creation tools, social networks and AI will lead to new ways to gather, organize and deliver media in engaging, personalized and interactive ways.

Low-resource communities: Investments in uplifting technologies like predictive models to prevent lead poisoning or improve food distributions could spread AI benefits to the underserved.

Public safety and security: Cameras, drones and software to analyze crime patterns should use AI in ways that reduce human bias and enhance safety without loss of liberty or dignity.

Employment and workplace: Work should start now on how to help people adapt as the economy undergoes rapid changes as many existing jobs are lost and new ones are created.

“Until now, most of what is known about AI comes from science fiction books and movies,” Stone said. “This study provides a realistic foundation to discuss how AI technologies are likely to affect society.”

Grosz said she hopes the AI 100 report “initiates a century-long conversation about ways AI-enhanced technologies might be shaped to improve life and societies.”

You can find the A100 website here, and the group’s first paper: “Artificial Intelligence and Life in 2030” here. Unfortunately, I don’t have time to read the report but I hope to do so soon.

The AI100 website’s About page offered a surprise,

This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

“Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

  • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
  • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;

    This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

    In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

    Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

    “Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

    Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

    • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
    • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;
    • Yoav Shoham, a professor of computer science at Stanford, who seeks to incorporate common sense into AI;
    • Tom Mitchell, the E. Fredkin University Professor and chair of the machine learning department at Carnegie Mellon University, whose studies include how computers might learn to read the Web;
    • and Alan Mackworth, a professor of computer science at the University of British Columbia [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

    I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

    Study Panels

    Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

    2015 Study Panel Members

    • Peter Stone, UT Austin, Chair
    • Rodney Brooks, Rethink Robotics
    • Erik Brynjolfsson, MIT
    • Ryan Calo, University of Washington
    • Oren Etzioni, Allen Institute for AI
    • Greg Hager, Johns Hopkins University
    • Julia Hirschberg, Columbia University
    • Shivaram Kalyanakrishnan, IIT Bombay
    • Ece Kamar, Microsoft
    • Sarit Kraus, Bar Ilan University
    • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
    • David Parkes, Harvard
    • Bill Press, UT Austin
    • AnnaLee (Anno) Saxenian, Berkeley
    • Julie Shah, MIT
    • Milind Tambe, USC
    • Astro Teller, Google[X]
  • [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

Study Panels

Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

2015 Study Panel Members

  • Peter Stone, UT Austin, Chair
  • Rodney Brooks, Rethink Robotics
  • Erik Brynjolfsson, MIT
  • Ryan Calo, University of Washington
  • Oren Etzioni, Allen Institute for AI
  • Greg Hager, Johns Hopkins University
  • Julia Hirschberg, Columbia University
  • Shivaram Kalyanakrishnan, IIT Bombay
  • Ece Kamar, Microsoft
  • Sarit Kraus, Bar Ilan University
  • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
  • David Parkes, Harvard
  • Bill Press, UT Austin
  • AnnaLee (Anno) Saxenian, Berkeley
  • Julie Shah, MIT
  • Milind Tambe, USC
  • Astro Teller, Google[X]

I see they have representation from Israel, India, and the private sector as well. Refreshingly, there’s more than one woman on the standing committee and in this first study group. It’s good to see these efforts at inclusiveness and I’m particularly delighted with the inclusion of an organization from Asia. All too often inclusiveness means Europe, especially the UK. So, it’s good (and I think important) to see a different range of representation.

As for the content of report, should anyone have opinions about it, please do let me know your thoughts in the blog comments.

The future of work during the age of robots and artificial intelligence

2014 was quite the year for discussions about robots/artificial intelligence (AI) taking over the world of work. There was my July 16, 2014 post titled, Writing and AI or is a robot writing this blog?, where I discussed the implications of algorithms which write news stories (business and sports, so far) in the wake of a deal that Associated Press signed with a company called Automated Insights. A few weeks later, the Pew Research Center released a report titled, AI, Robotics, and the Future of Jobs, which was widely covered. As well, sometime during the year, renowned physicist Stephen Hawking expressed serious concerns about artificial intelligence and our ability to control it.

It seems that 2015 is going to be another banner for this discussion. Before launching into the latest on this topic, here’s a sampling of the Pew Research and the response to it. From an Aug. 6, 2014 Pew summary about AI, Robotics, and the Future of Jobs by Aaron Smith and Janna Anderson,

The vast majority of respondents to the 2014 Future of the Internet canvassing anticipate that robotics and artificial intelligence will permeate wide segments of daily life by 2025, with huge implications for a range of industries such as health care, transport and logistics, customer service, and home maintenance. But even as they are largely consistent in their predictions for the evolution of technology itself, they are deeply divided on how advances in AI and robotics will impact the economic and employment picture over the next decade.

We call this a canvassing because it is not a representative, randomized survey. Its findings emerge from an “opt in” invitation to experts who have been identified by researching those who are widely quoted as technology builders and analysts and those who have made insightful predictions to our previous queries about the future of the Internet. …

I wouldn’t have expected Jeff Bercovici’s Aug. 6, 2014 article for Forbes to be quite so hesitant about the possibilities of our robotic and artificially intelligent future,

As part of a major ongoing project looking at the future of the internet, the Pew Research Internet Project canvassed some 1,896 technologists, futurists and other experts about how they see advances in robotics and artificial intelligence affecting the human workforce in 2025.

The results were not especially reassuring. Nearly half of the respondents (48%) predicted that robots and AI will displace more jobs than they create over the coming decade. While that left a slim majority believing the impact of technology on employment will be neutral or positive, that’s not necessarily grounds for comfort: Many experts told Pew they expect the jobs created by the rise of the machines will be lower paying and less secure than the ones displaced, widening the gap between rich and poor, while others said they simply don’t think the major effects of robots and AI, for better or worse, will be in evidence yet by 2025.

Chris Gayomali’s Aug. 6, 2014 article for Fast Company poses an interesting question about how this brave new future will be financed,

A new study by Pew Internet Research takes a hard look at how innovations in robotics and artificial intelligence will impact the future of work. To reach their conclusions, Pew researchers invited 12,000 experts (academics, researchers, technologists, and the like) to answer two basic questions:

Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?
To what degree will AI and robotics be parts of the ordinary landscape of the general population by 2025?

Close to 1,900 experts responded. About half (48%) of the people queried envision a future in which machines have displaced both blue- and white-collar jobs. It won’t be so dissimilar from the fundamental shift we saw in manufacturing, in which fewer (human) bosses oversaw automated assembly lines.

Meanwhile, the other 52% of experts surveyed speculate while that many of the jobs will be “substantially taken over by robots,” humans won’t be displaced outright. Rather, many people will be funneled into new job categories that don’t quite exist yet. …

Some worry that over the next 10 years, we’ll see a large number of middle class jobs disappear, widening the economic gap between the rich and the poor. The shift could be dramatic. As artificial intelligence becomes less artificial, they argue, the worry is that jobs that earn a decent living wage (say, customer service representatives, for example) will no longer be available, putting lots and lots of people out of work, possibly without the requisite skill set to forge new careers for themselves.

How do we avoid this? One revealing thread suggested by experts argues that the responsibility will fall on businesses to protect their employees. “There is a relentless march on the part of commercial interests (businesses) to increase productivity so if the technical advances are reliable and have a positive ROI [return on investment],” writes survey respondent Glenn Edens, a director of research in networking, security, and distributed systems at PARC, which is owned by Xerox. “Ultimately we need a broad and large base of employed population, otherwise there will be no one to pay for all of this new world.” [emphasis mine]

Alex Hearn’s Aug. 6, 2014 article for the Guardian reviews the report and comments on the current educational system’s ability to prepare students for the future,

Almost all of the respondents are united on one thing: the displacement of work by robots and AI is going to continue, and accelerate, over the coming decade. Where they split is in the societal response to that displacement.

The optimists predict that the economic boom that would result from vastly reduced costs to businesses would lead to the creation of new jobs in huge numbers, and a newfound premium being placed on the value of work that requires “uniquely human capabilities”. …

But the pessimists worry that the benefits of the labor replacement will accrue to those already wealthy enough to own the automatons, be that in the form of patents for algorithmic workers or the physical form of robots.

The ranks of the unemployed could swell, as people are laid off from work they are qualified in without the ability to retrain for careers where their humanity is a positive. And since this will happen in every economic sector simultaneously, civil unrest could be the result.

One thing many experts agreed on was the need for education to prepare for a post-automation world. ““Only the best-educated humans will compete with machines,” said internet sociologist Howard Rheingold.

“And education systems in the US and much of the rest of the world are still sitting students in rows and columns, teaching them to keep quiet and memorise what is told them, preparing them for life in a 20th century factory.”

Then, Will Oremus’ Aug. 6, 2014 article for Slate suggests we are already experiencing displacement,

… the current jobless recovery, along with a longer-term trend toward income and wealth inequality, has some thinkers wondering whether the latest wave of automation is different from those that preceded it.

Massachusetts Institute of Technology researchers Andrew McAfee and Erik Brynjolfsson, among others, see a “great decoupling” of productivity from wages since about 2000 as technology outpaces human workers’ education and skills. Workers, in other words, are losing the race between education and technology. This may be exacerbating a longer-term trend in which capital has gained the upper hand on labor since the 1970s.

The results of the survey were fascinating. Almost exactly half of the respondents (48 percent) predicted that intelligent software will disrupt more jobs than it can replace. The other half predicted the opposite.

The lack of expert consensus on such a crucial and seemingly straightforward question is startling. It’s even more so given that history and the leading economic models point so clearly to one side of the question: the side that reckons society will adjust, new jobs will emerge, and technology will eventually leave the economy stronger.

More recently, Manish Singh has written about some of his concerns as a writer who could be displaced in a Jan. 31, 2015 (?) article for Beta News (Note: A link has been removed),

Robots are after my job. They’re after yours as well, but let us deal with my problem first. Associated Press, an American multinational nonprofit news agency, revealed on Friday [Jan. 30, 2015] that it published 3,000 articles in the last three months of 2014. The company could previously only publish 300 stories. It didn’t hire more journalists, neither did its existing headcount start writing more, but the actual reason behind this exponential growth is technology. All those stories were written by an algorithm.

The articles produced by the algorithm were accurate, and you won’t be able to separate them from stories written by humans. Good lord, all the stories were written in accordance with the AP Style Guide, something not all journalists follow (but arguably, should).

There has been a growth in the number of such software. Narrative Science, a Chicago-based company offers an automated narrative generator powered by artificial intelligence. The company’s co-founder and CTO, Kristian Hammond, said last year that he believes that by 2030, 90 percent of news could be written by computers. Forbes, a reputable news outlet, has used Narrative’s software. Some news outlets use it to write email newsletters and similar things.

Singh also sounds a note of concern for other jobs by including this video (approximately 16 mins.) in his piece,

This video (Humans Need Not Apply) provides an excellent overview of the situation although it seems C. G. P. Grey, the person who produced and posted the video on YouTube, holds a more pessimistic view of the future than some other futurists.  C. G. P. Grey has a website here and is profiled here on Wikipedia.

One final bit, there’s a robot art critic which some are suggesting is superior to human art critics in Thomas Gorton’s Jan. 16, 2015 (?) article ‘This robot reviews art better than most critics‘ for Dazed Digital (Note: Links have been removed),

… the Novice Art Blogger, a Tumblr page set up by Matthew Plummer Fernandez. The British-Colombian artist programmed a bot with deep learning algorithms to analyse art; so instead of an overarticulate critic rambling about praxis, you get a review that gets down to the nitty-gritty about what exactly you see in front of you.

The results are charmingly honest: think a round robin of Google Translate text uninhibited by PR fluff, personal favouritism or the whims of a bad mood. We asked Novice Art Blogger to review our most recent Winter 2014 cover with Kendall Jenner. …

Beyond Kendall Jenner, it’s worth reading Gorton’s article for the interview with Plummer Fernandez.