Tag Archives: Watson

How to get people to trust artificial intelligence

Vyacheslav Polonski’s (University of Oxford researcher) January 10, 2018 piece (originally published Jan. 9, 2018 on The Conversation) on phys.org isn’t a gossip article although there are parts that could be read that way. Before getting to what I consider the juicy bits (Note: Links have been removed),

Artificial intelligence [AI] can already predict the future. Police forces are using it to map when and where crime is likely to occur [Note: See my Nov. 23, 2017 posting about predictive policing in Vancouver for details about the first Canadian municipality to introduce the technology]. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences.

Many decisions in our lives require a good forecast, and AI agents are almost always better at forecasting than their human counterparts. Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions. Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if these experts are wrong.

The part (juicy bits) that satisfied some of my long held curiosity was this section on Watson and its life as a medical adjunct (Note: Links have been removed),

IBM’s attempt to promote its supercomputer programme to cancer doctors (Watson for Onology) was a PR [public relations] disaster. The AI promised to deliver top-quality recommendations on the treatment of 12 cancers that accounted for 80% of the world’s cases. As of today, over 14,000 patients worldwide have received advice based on its calculations.

But when doctors first interacted with Watson they found themselves in a rather difficult situation. On the one hand, if Watson provided guidance about a treatment that coincided with their own opinions, physicians did not see much value in Watson’s recommendations. The supercomputer was simply telling them what they already know, and these recommendations did not change the actual treatment. This may have given doctors some peace of mind, providing them with more confidence in their own decisions. But IBM has yet to provide evidence that Watson actually improves cancer survival rates.

On the other hand, if Watson generated a recommendation that contradicted the experts’ opinion, doctors would typically conclude that Watson wasn’t competent. And the machine wouldn’t be able to explain why its treatment was plausible because its machine learning algorithms were simply too complex to be fully understood by humans. Consequently, this has caused even more mistrust and disbelief, leading many doctors to ignore the seemingly outlandish AI recommendations and stick to their own expertise.

As a result, IBM Watson’s premier medical partner, the MD Anderson Cancer Center, recently announced it was dropping the programme. Similarly, a Danish hospital reportedly abandoned the AI programme after discovering that its cancer doctors disagreed with Watson in over two thirds of cases.

The problem with Watson for Oncology was that doctors simply didn’t trust it. Human trust is often based on our understanding of how other people think and having experience of their reliability. …

It seems to me there might be a bit more to the doctors’ trust issues and I was surprised it didn’t seem to have occurred to Polonski. Then I did some digging (from Polonski’s webpage on the Oxford Internet Institute website),

Vyacheslav Polonski (@slavacm) is a DPhil [PhD] student at the Oxford Internet Institute. His research interests are located at the intersection of network science, media studies and social psychology. Vyacheslav’s doctoral research examines the adoption and use of social network sites, focusing on the effects of social influence, social cognition and identity construction.

Vyacheslav is a Visiting Fellow at Harvard University and a Global Shaper at the World Economic Forum. He was awarded the Master of Science degree with Distinction in the Social Science of the Internet from the University of Oxford in 2013. He also obtained the Bachelor of Science degree with First Class Honours in Management from the London School of Economics and Political Science (LSE) in 2012.

Vyacheslav was honoured at the British Council International Student of the Year 2011 awards, and was named UK’s Student of the Year 2012 and national winner of the Future Business Leader of the Year 2012 awards by TARGETjobs.

Previously, he has worked as a management consultant at Roland Berger Strategy Consultants and gained further work experience at the World Economic Forum, PwC, Mars, Bertelsmann and Amazon.com. Besides, he was involved in several start-ups as part of the 2012 cohort of Entrepreneur First and as part of the founding team of the London office of Rocket Internet. Vyacheslav was the junior editor of the bi-lingual book ‘Inspire a Nation‘ about Barack Obama’s first presidential election campaign. In 2013, he was invited to be a keynote speaker at the inaugural TEDx conference of IE University in Spain to discuss the role of a networked mindset in everyday life.

Vyacheslav is fluent in German, English and Russian, and is passionate about new technologies, social entrepreneurship, philanthropy, philosophy and modern art.

Research interests

Network science, social network analysis, online communities, agency and structure, group dynamics, social interaction, big data, critical mass, network effects, knowledge networks, information diffusion, product adoption

Positions held at the OII

DPhil student, October 2013 –

MSc Student, October 2012 – August 2013

Polonski doesn’t seem to have any experience dealing with, participating in, or studying the medical community. Getting a doctor to admit that his or her approach to a particular patient’s condition was wrong or misguided runs counter to their training and, by extension, the institution of medicine. Also, one of the biggest problems in any field is getting people to change and it’s not always about trust. In this instance, you’re asking a doctor to back someone else’s opinion after he or she has rendered theirs. This is difficult even when the other party is another human doctor let alone a form of artificial intelligence.

If you want to get a sense of just how hard it is to get someone to back down after they’ve committed to a position, read this January 10, 2018 essay by Lara Bazelon, an associate professor at the University of San Francisco School of Law. This is just one of the cases (Note: Links have been removed),

Davontae Sanford was 14 years old when he confessed to murdering four people in a drug house on Detroit’s East Side. Left alone with detectives in a late-night interrogation, Sanford says he broke down after being told he could go home if he gave them “something.” On the advice of a lawyer whose license was later suspended for misconduct, Sanders pleaded guilty in the middle of his March 2008 trial and received a sentence of 39 to 92 years in prison.

Sixteen days after Sanford was sentenced, a hit man named Vincent Smothers told the police he had carried out 12 contract killings, including the four Sanford had pleaded guilty to committing. Smothers explained that he’d worked with an accomplice, Ernest Davis, and he provided a wealth of corroborating details to back up his account. Smothers told police where they could find one of the weapons used in the murders; the gun was recovered and ballistics matched it to the crime scene. He also told the police he had used a different gun in several of the other murders, which ballistics tests confirmed. Once Smothers’ confession was corroborated, it was clear Sanford was innocent. Smothers made this point explicitly in an 2015 affidavit, emphasizing that Sanford hadn’t been involved in the crimes “in any way.”

Guess what happened? (Note: Links have been removed),

But Smothers and Davis were never charged. Neither was Leroy Payne, the man Smothers alleged had paid him to commit the murders. …

Davontae Sanford, meanwhile, remained behind bars, locked up for crimes he very clearly didn’t commit.

Police failed to turn over all the relevant information in Smothers’ confession to Sanford’s legal team, as the law required them to do. When that information was leaked in 2009, Sanford’s attorneys sought to reverse his conviction on the basis of actual innocence. Wayne County Prosecutor Kym Worthy fought back, opposing the motion all the way to the Michigan Supreme Court. In 2014, the court sided with Worthy, ruling that actual innocence was not a valid reason to withdraw a guilty plea [emphasis mine]. Sanford would remain in prison for another two years.

…

Doctors are just as invested in their opinions and professional judgments as lawyers (just like the prosecutor and the judges on the Michigan Supreme Court) are.

There is one more problem. From the doctor’s (or anyone else’s perspective), if the AI is making the decisions, why do he/she need to be there? At best it’s as if AI were turning the doctor into its servant or, at worst, replacing the doctor. Polonski alludes to the problem in one of his solutions to the ‘trust’ issue (Note: A link has been removed),

…

Research suggests involving people more in the AI decision-making process could also improve trust and allow the AI to learn from human experience. For example,one study showed people were given the freedom to slightly modify an algorithm felt more satisfied with its decisions, more likely to believe it was superior and more likely to use it in the future.

…

Having input into the AI decision-making process somewhat addresses one of the problems but the commitment to one’s own judgment even when there is overwhelming evidence to the contrary is a perennially thorny problem. The legal case mentioned here earlier is clearly one where the contrarian is wrong but it’s not always that obvious. As well, sometimes, people who hold out against the majority are right.

US Army

Getting back to building trust, it turns out the US Army Research Laboratory is also interested in transparency where AI is concerned (from a January 11, 2018 US Army news release on EurekAlert),

U.S. Army Research Laboratory [ARL] scientists developed ways to improve collaboration between humans and artificially intelligent agents in two projects recently completed for the Autonomy Research Pilot Initiative supported by the Office of Secretary of Defense. They did so by enhancing the agent transparency [emphasis mine], which refers to a robot, unmanned vehicle, or software agent’s ability to convey to humans its intent, performance, future plans, and reasoning process.

“As machine agents become more sophisticated and independent, it is critical for their human counterparts to understand their intent, behaviors, reasoning process behind those behaviors, and expected outcomes so the humans can properly calibrate their trust [emphasis mine] in the systems and make appropriate decisions,” explained ARL’s Dr. Jessie Chen, senior research psychologist.

The U.S. Defense Science Board, in a 2016 report, identified six barriers to human trust in autonomous systems, with ‘low observability, predictability, directability and auditability’ as well as ‘low mutual understanding of common goals’ being among the key issues.

In order to address these issues, Chen and her colleagues developed the Situation awareness-based Agent Transparency, or SAT, model and measured its effectiveness on human-agent team performance in a series of human factors studies supported by the ARPI. The SAT model deals with the information requirements from an agent to its human collaborator in order for the human to obtain effective situation awareness of the agent in its tasking environment. At the first SAT level, the agent provides the operator with the basic information about its current state and goals, intentions, and plans. At the second level, the agent reveals its reasoning process as well as the constraints/affordances that the agent considers when planning its actions. At the third SAT level, the agent provides the operator with information regarding its projection of future states, predicted consequences, likelihood of success/failure, and any uncertainty associated with the aforementioned projections.

In one of the ARPI projects, IMPACT, a research program on human-agent teaming for management of multiple heterogeneous unmanned vehicles, ARL’s experimental effort focused on examining the effects of levels of agent transparency, based on the SAT model, on human operators’ decision making during military scenarios. The results of a series of human factors experiments collectively suggest that transparency on the part of the agent benefits the human’s decision making and thus the overall human-agent team performance. More specifically, researchers said the human’s trust in the agent was significantly better calibrated — accepting the agent’s plan when it is correct and rejecting it when it is incorrect– when the agent had a higher level of transparency.

The other project related to agent transparency that Chen and her colleagues performed under the ARPI was Autonomous Squad Member, on which ARL collaborated with Naval Research Laboratory scientists. The ASM is a small ground robot that interacts with and communicates with an infantry squad. As part of the overall ASM program, Chen’s group developed transparency visualization concepts, which they used to investigate the effects of agent transparency levels on operator performance. Informed by the SAT model, the ASM’s user interface features an at a glance transparency module where user-tested iconographic representations of the agent’s plans, motivator, and projected outcomes are used to promote transparent interaction with the agent. A series of human factors studies on the ASM’s user interface have investigated the effects of agent transparency on the human teammate’s situation awareness, trust in the ASM, and workload. The results, consistent with the IMPACT project’s findings, demonstrated the positive effects of agent transparency on the human’s task performance without increase of perceived workload. The research participants also reported that they felt the ASM as more trustworthy, intelligent, and human-like when it conveyed greater levels of transparency.

Chen and her colleagues are currently expanding the SAT model into bidirectional transparency between the human and the agent.

“Bidirectional transparency, although conceptually straightforward–human and agent being mutually transparent about their reasoning process–can be quite challenging to implement in real time. However, transparency on the part of the human should support the agent’s planning and performance–just as agent transparency can support the human’s situation awareness and task performance, which we have demonstrated in our studies,” Chen hypothesized.

The challenge is to design the user interfaces, which can include visual, auditory, and other modalities, that can support bidirectional transparency dynamically, in real time, while not overwhelming the human with too much information and burden.

Interesting, yes? Here’s a link and a citation for the paper,

Situation Awareness-based Agent Transparency and Human-Autonomy Teaming Effectiveness by Jessie Y.C. Chen, Shan G. Lakhmani, Kimberly Stowers, Anthony R. Selkowitz, Julia L. Wright, and Michael Barnes. Theoretical Issues in Ergonomics Science May 2018. DOI 10.1080/1463922X.2017.1315750

This paper is behind a paywall.

Health technology and the Canadian Broadcasting Corporation’s (CBC) two-tier health system ‘Viewpoint’

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There’s a lot of talk and handwringing about Canada’s health care system, which ebbs and flows in almost predictable cycles. Jesse Hirsh in a May 16, 2017 ‘Viewpoints’ segment (an occasional series run as part the of the CBC’s [Canadian Broadcasting Corporation] flagship, daily news programme, The National) dared to reframe the discussion as one about technology and ‘those who get it’ [the technologically literate] and ‘those who don’t’, a state Hirsh described as being illiterate as you can see and hear in the following video.

I don’t know about you but I’m getting tired of being called illiterate when I don’t know something. To be illiterate means you can’t read and write and as it turns out I do both of those things on a daily basis (sometimes even in two languages). Despite my efforts, I’m ignorant about any number of things and those numbers keep increasing day by day. BTW, Is there anyone who isn’t having trouble keeping up?

Moving on from my rhetorical question, Hirsh has a point about the tech divide and about the need for discussion. It’s a point that hadn’t occurred to me (although I think he’s taking it in the wrong direction). In fact, this business of a tech divide already exists if you consider that people who live in rural environments and need the latest lifesaving techniques or complex procedures or access to highly specialized experts have to travel to urban centres. I gather that Hirsh feels that this divide isn’t necessarily going to be an urban/rural split so much as an issue of how technically literate you and your doctor are. That’s intriguing but then his argumentation gets muddled. Confusingly, he seems to be suggesting that the key to the split is your access (not your technical literacy) to artificial intelligence (AI) and algorithms (presumably he’s referring to big data and data analytics). I expect access will come down more to money than technological literacy.

For example, money is likely to be a key issue when you consider his big pitch is for access to IBM’s Watson computer. (My Feb. 28, 2011 posting titled: Engineering, entertainment, IBM’s Watson, and product placement focuses largely on Watson, its winning appearances on the US television game show, Jeopardy, and its subsequent adoption into the University of Maryland’s School of Medicine in a project to bring Watson into the examining room with patients.)

Hirsh’s choice of IBM’s Watson is particularly interesting for a number of reasons. (1) Presumably there are companies other than IBM in this sector. Why do they not rate a mention? (2) Given the current situation with IBM and the Canadian federal government’s introduction of the Phoenix payroll system (a PeopleSoft product customized by IBM), which is a failure of monumental proportions (a Feb. 23, 2017 article by David Reevely for the Ottawa Citizen and a May 25, 2017 article by Jordan Press for the National Post), there may be a little hesitation, if not downright resistance, to a large scale implementation of any IBM product or service, regardless of where the blame lies. (3) Hirsh notes on the home page for his eponymous website,

I’m presently spending time at the IBM Innovation Space in Toronto Canada, investigating the impact of artificial intelligence and cognitive computing on all sectors and industries.

Yes, it would seem he has some sort of relationship with IBM not referenced in his Viewpoints segment on The National. Also, his description of the relationship isn’t especially illuminating but perhaps it.s this? (from the IBM Innovation Space – Toronto Incubator Application webpage),

Our incubator

The IBM Innovation Space is a Toronto-based incubator that provides startups with a collaborative space to innovate and disrupt the market. Our goal is to provide you with the tools needed to take your idea to the next level, introduce you to the right networks and help you acquire new clients. Our unique approach, specifically around client engagement, positions your company for optimal growth and revenue at an accelerated pace.

…

OUR SERVICES

IBM Bluemix
IBM Global Entrepreneur
Softlayer – an IBM Company
Watson

Startups partnered with the IBM Innovation Space can receive up to $120,000 in IBM credits at no charge for up to 12 months through the Global Entrepreneurship Program (GEP). These credits can be used in our products such our IBM Bluemix developer platform, Softlayer cloud services, and our world-renowned IBM Watson ‘cognitive thinking’ APIs. We provide you with enterprise grade technology to meet your clients’ needs, large or small.

Collaborative workspace in the heart of Downtown Toronto
Mentorship opportunities available with leading experts
Access to large clients to scale your startup quickly and effectively
Weekly programming ranging from guest speakers to collaborative activities
Help with funding and access to local VCs and investors

Final comments

While I have some issues with Hirsh’s presentation, I agree that we should be discussing the issues around increased automation of our health care system. A friend of mine’s husband is a doctor and according to him those prescriptions and orders you get when leaving the hospital? They are not made up by a doctor so much as they are spit up by a computer based on the data that the doctors and nurses have supplied.

GIGO, bias, and de-skilling

Leaving aside the wonders that Hirsh describes, there’s an oldish saying in the computer business, garbage in/garbage out (gigo). At its simplest, who’s going to catch a mistake? (There are lots of mistakes made in hospitals and other health care settings.)

There are also issues around the quality of research. Are all the research papers included in the data used by the algorithms going to be considered equal? There’s more than one case where a piece of problematic research has been accepted uncritically, even if it get through peer review, and subsequently cited many times over. One of the ways to measure impact, i.e., importance, is to track the number of citations. There’s also the matter of where the research is published. A ‘high impact’ journal, such as Nature, Science, or Cell, automatically gives a piece of research a boost.

There are other kinds of bias as well. Increasingly, there’s discussion about algorithms being biased and about how machine learning (AI) can become biased. (See my May 24, 2017 posting: Machine learning programs learn bias, which highlights the issues and cites other FrogHeart posts on that and other related topics.)

These problems are to a large extent already present. Doctors have biases and research can be wrong and it can take a long time before there are corrections. However, the advent of an automated health diagnosis and treatment system is likely to exacerbate the problems. For example, if you don’t agree with your doctor’s diagnosis or treatment, you can search other opinions. What happens when your diagnosis and treatment have become data? Will the system give you another opinion? Who will you talk to? The doctor who got an answer from ‘Watson”? Is she or he going to debate Watson? Are you?

This leads to another issue and that’s automated systems getting more credit than they deserve. Futurists such as Hirsh tend to underestimate people and overestimate the positive impact that automation will have. A computer, data analystics, or an AI system are tools not gods. You’ll have as much luck petitioning one of those tools as you would Zeus.

The unasked question is how will your doctor or other health professional gain experience and skills if they never have to practice the basic, boring aspects of health care (asking questions for a history, reading medical journals to keep up with the research, etc.) and leave them to the computers? There had to be a reason for calling it a medical ‘practice’.

There are definitely going to be advantages to these technological innovations but thoughtful adoption of these practices (pun intended) should be our goal.

Who owns your data?

Another issue which is increasingly making itself felt is ownership of data. Jacob Brogan has written a provocative May 23, 2017 piece for slate.com asking that question about the data Ancestry.com gathers for DNA testing (Note: Links have been removed),

AncestryDNA’s pitch to consumers is simple enough. For $99 (US), the company will analyze a sample of your saliva and then send back information about your “ethnic mix.” While that promise may be scientifically dubious, it’s a relatively clear-cut proposal. Some, however, worry that the service might raise significant privacy concerns.

After surveying AncestryDNA’s terms and conditions, consumer protection attorney Joel Winston found a few issues that troubled him. As he noted in a Medium post last week, the agreement asserts that it grants the company “a perpetual, royalty-free, world-wide, transferable license to use your DNA.” (The actual clause is considerably longer.) According to Winston, “With this single contractual provision, customers are granting Ancestry.com the broadest possible rights to own and exploit their genetic information.”

…

Winston also noted a handful of other issues that further complicate the question of ownership. Since we share much of our DNA with our relatives, he warned, “Even if you’ve never used Ancestry.com, but one of your genetic relatives has, the company may already own identifiable portions of your DNA.” [emphasis mine] Theoretically, that means information about your genetic makeup could make its way into the hands of insurers or other interested parties, whether or not you’ve sent the company your spit. (Maryam Zaringhalam explored some related risks in a recent Slate article.) Further, Winston notes that Ancestry’s customers waive their legal rights, meaning that they cannot sue the company if their information gets used against them in some way.

Over the weekend, Eric Heath, Ancestry’s chief privacy officer, responded to these concerns on the company’s own site. He claims that the transferable license is necessary for the company to provide its customers with the service that they’re paying for: “We need that license in order to move your data through our systems, render it around the globe, and to provide you with the results of our analysis work.” In other words, it allows them to send genetic samples to labs (Ancestry uses outside vendors), store the resulting data on servers, and furnish the company’s customers with the results of the study they’ve requested.

Speaking to me over the phone, Heath suggested that this license was akin to the ones that companies such as YouTube employ when users upload original content. It grants them the right to shift that data around and manipulate it in various ways, but isn’t an assertion of ownership. “We have committed to our users that their DNA data is theirs. They own their DNA,” he said.

…

I’m glad to see the company’s representatives are open to discussion and, later in the article, you’ll see there’ve already been some changes made. Still, there is no guarantee that the situation won’t again change, for ill this time.

What data do they have and what can they do with it?

It’s not everybody who thinks data collection and data analytics constitute problems. While some people might balk at the thought of their genetic data being traded around and possibly used against them, e.g., while hunting for a job, or turned into a source of revenue, there tends to be a more laissez-faire attitude to other types of data. Andrew MacLeod’s May 24, 2017 article for thetyee.ca highlights political implications and privacy issues (Note: Links have been removed),

After a small Victoria [British Columbia, Canada] company played an outsized role in the Brexit vote, government information and privacy watchdogs in British Columbia and Britain have been consulting each other about the use of social media to target voters based on their personal data.

The U.K.’s information commissioner, Elizabeth Denham [Note: Denham was formerly B.C.’s Office of the Information and Privacy Commissioner], announced last week [May 17, 2017] that she is launching an investigation into “the use of data analytics for political purposes.”

The investigation will look at whether political parties or advocacy groups are gathering personal information from Facebook and other social media and using it to target individuals with messages, Denham said.

B.C.’s Office of the Information and Privacy Commissioner confirmed it has been contacted by Denham.

Macleod’s March 6, 2017 article for thetyee.ca provides more details about the company’s role (note: Links have been removed),

The “tiny” and “secretive” British Columbia technology company [AggregateIQ; AIQ] that played a key role in the Brexit referendum was until recently listed as the Canadian office of a much larger firm that has 25 years of experience using behavioural research to shape public opinion around the world.

The larger firm, SCL Group, says it has worked to influence election outcomes in 19 countries. Its associated company in the U.S., Cambridge Analytica, has worked on a wide range of campaigns, including Donald Trump’s presidential bid.

In late February [2017], the Telegraph reported that campaign disclosures showed that Vote Leave campaigners had spent £3.5 million — about C$5.75 million [emphasis mine] — with a company called AggregateIQ, run by CEO Zack Massingham in downtown Victoria.

That was more than the Leave side paid any other company or individual during the campaign and about 40 per cent of its spending ahead of the June referendum that saw Britons narrowly vote to exit the European Union.

…

According to media reports, Aggregate develops advertising to be used on sites including Facebook, Twitter and YouTube, then targets messages to audiences who are likely to be receptive.

…

The Telegraph story described Victoria as “provincial” and “picturesque” and AggregateIQ as “secretive” and “low-profile.”

Canadian media also expressed surprise at AggregateIQ’s outsized role in the Brexit vote.

The Globe and Mail’s Paul Waldie wrote “It’s quite a coup for Mr. Massingham, who has only been involved in politics for six years and started AggregateIQ in 2013.”

Victoria Times Colonist columnist Jack Knox wrote “If you have never heard of AIQ, join the club.”

The Victoria company, however, appears to be connected to the much larger SCL Group, which describes itself on its website as “the global leader in data-driven communications.”

In the United States it works through related company Cambridge Analytica and has been involved in elections since 2012. Politico reported in 2015 that the firm was working on Ted Cruz’s presidential primary campaign.

And NBC and other media outlets reported that the Trump campaign paid Cambridge Analytica millions to crunch data on 230 million U.S. adults, using information from loyalty cards, club and gym memberships and charity donations [emphasis mine] to predict how an individual might vote and to shape targeted political messages.

…

That’s quite a chunk of change and I don’t believe that gym memberships, charity donations, etc. were the only sources of information (in the US, there’s voter registration, credit card information, and more) but the list did raise my eyebrows. It would seem we are under surveillance at all times, even in the gym.

In any event, I hope that Hirsh’s call for discussion is successful and that the discussion includes more critical thinking about the implications of Hirsh’s ‘Brave New World’.

Westworld: a US television programme investigating AI (artificial intelligence) and consciousness

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The US television network, Home Box Office (HBO) is getting ready to première Westworld, a new series based on a movie first released in 1973. Here’s more about the movie from its Wikipedia entry (Note: Links have been removed),

Westworld is a 1973 science fiction Western thriller film written and directed by novelist Michael Crichton and produced by Paul Lazarus III about amusement park robots that malfunction and begin killing visitors. It stars Yul Brynner as an android in a futuristic Western-themed amusement park, and Richard Benjamin and James Brolin as guests of the park.

Westworld was the first theatrical feature directed by Michael Crichton.[3] It was also the first feature film to use digital image processing, to pixellate photography to simulate an android point of view.[4] The film was nominated for Hugo, Nebula and Saturn awards, and was followed by a sequel film, Futureworld, and a short-lived television series, Beyond Westworld. In August 2013, HBO announced plans for a television series based on the original film.

The latest version is due to start broadcasting in the US on Sunday, Oct. 2, 2016 and as part of the publicity effort the producers are profiled by Sean Captain for Fast Company in a Sept. 30, 2016 article,

As Game of Thrones marches into its final seasons, HBO is debuting this Sunday what it hopes—and is betting millions of dollars on—will be its new blockbuster series: Westworld, a thorough reimagining of Michael Crichton’s 1973 cult classic film about a Western theme park populated by lifelike robot hosts. A philosophical prelude to Jurassic Park, Crichton’s Westworld is a cautionary tale about technology gone very wrong: the classic tale of robots that rise up and kill the humans. HBO’s new series, starring Evan Rachel Wood, Anthony Hopkins, and Ed Harris, is subtler and also darker: The humans are the scary ones.

“We subverted the entire premise of Westworld in that our sympathies are meant to be with the robots, the hosts,” says series co-creator Lisa Joy. She’s sitting on a couch in her Burbank office next to her partner in life and on the show—writer, director, producer, and husband Jonathan Nolan—who goes by Jonah. …

Their Westworld, which runs in the revered Sunday-night 9 p.m. time slot, combines present-day production values and futuristic technological visions—thoroughly revamping Crichton’s story with hybrid mechanical-biological robots [emphasis mine] fumbling along the blurry line between simulated and actual consciousness.

Captain never does explain the “hybrid mechanical-biological robots.” For example, do they have human skin or other organs grown for use in a robot? In other words, how are they hybrid?

That nitpick aside, the article provides some interesting nuggets of information and insight into the themes and ideas 2016 Westworld’s creators are exploring (Note: A link has been removed),

… Based on the four episodes I previewed (which get progressively more interesting), Westworld does a good job with the trope—which focused especially on the awakening of Dolores, an old soul of a robot played by Evan Rachel Wood. Dolores is also the catchall Spanish word for suffering, pain, grief, and other displeasures. “There are no coincidences in Westworld,” says Joy, noting that the name is also a play on Dolly, the first cloned mammal.

The show operates on a deeper, though hard-to-define level, that runs beneath the shoot-em and screw-em frontier adventure and robotic enlightenment narratives. It’s an allegory of how even today’s artificial intelligence is already taking over, by cataloging and monetizing our lives and identities. “Google and Facebook, their business is reading your mind in order to advertise shit to you,” says Jonah Nolan. …

…

“Exist free of rules, laws or judgment. No impulse is taboo,” reads a spoof home page for the resort that HBO launched a few weeks ago. That’s lived to the fullest by the park’s utterly sadistic loyal guest, played by Ed Harris and known only as the Man in Black.

The article also features some quotes from scientists on the topic of artificial intelligence (Note: Links have been removed),

“In some sense, being human, but less than human, it’s a good thing,” says Jon Gratch, professor of computer science and psychology at the University of Southern California [USC]. Gratch directs research at the university’s Institute for Creative Technologies on “virtual humans,” AI-driven onscreen avatars used in military-funded training programs. One of the projects, SimSensei, features an avatar of a sympathetic female therapist, Ellie. It uses AI and sensors to interpret facial expressions, posture, tension in the voice, and word choices by users in order to direct a conversation with them.

“One of the things that we’ve found is that people don’t feel like they’re being judged by this character,” says Gratch. In work with a National Guard unit, Ellie elicited more honest responses about their psychological stresses than a web form did, he says. Other data show that people are more honest when they know the avatar is controlled by an AI versus being told that it was controlled remotely by a human mental health clinician.

…

“If you build it like a human, and it can interact like a human. That solves a lot of the human-computer or human-robot interaction issues,” says professor Paul Rosenbloom, also with USC’s Institute for Creative Technologies. He works on artificial general intelligence, or AGI—the effort to create a human-like or human level of intellect.

Rosenbloom is building an AGI platform called Sigma that models human cognition, including emotions. These could make a more effective robotic tutor, for instance, “There are times you want the person to know you are unhappy with them, times you want them to know that you think they’re doing great,” he says, where “you” is the AI programmer. “And there’s an emotional component as well as the content.”

Achieving full AGI could take a long time, says Rosenbloom, perhaps a century. Bernie Meyerson, IBM’s chief innovation officer, is also circumspect in predicting if or when Watson could evolve into something like HAL or Her. “Boy, we are so far from that reality, or even that possibility, that it becomes ludicrous trying to get hung up there, when we’re trying to get something to reasonably deal with fact-based data,” he says.

Gratch, Rosenbloom, and Meyerson are talking about screen-based entities and concepts of consciousness and emotions. Then, there’s a scientist who’s talking about the difficulties with robots,

…

… Ken Goldberg, an artist and professor of engineering at UC [University of California] Berkeley, calls the notion of cyborg robots in Westworld “a pretty common trope in science fiction.” (Joy will take up the theme again, as the screenwriter for a new Battlestar Galactica movie.) Goldberg’s lab is struggling just to build and program a robotic hand that can reliably pick things up. But a sympathetic, somewhat believable Dolores in a virtual setting is not so farfetched.

Captain delves further into a thorny issue,

“Can simulations, at some point, become the real thing?” asks Patrick Lin, director of the Ethics + Emerging Sciences Group at California Polytechnic State University. “If we perfectly simulate a rainstorm on a computer, it’s still not a rainstorm. We won’t get wet. But is the mind or consciousness different? The jury is still out.”

…

While artificial consciousness is still in the dreamy phase, today’s level of AI is serious business. “What was sort of a highfalutin philosophical question a few years ago has become an urgent industrial need,” says Jonah Nolan. It’s not clear yet how the Delos management intends, beyond entrance fees, to monetize Westworld, although you get a hint when Ford tells Theresa Cullen “We know everything about our guests, don’t we? As we know everything about our employees.”

AI has a clear moneymaking model in this world, according to Nolan. “Facebook is monetizing your social graph, and Google is advertising to you.” Both companies (and others) are investing in AI to better understand users and find ways to make money off this knowledge. …

As my colleague David Bruggeman has often noted on his Pasco Phronesis blog, there’s a lot of science on television.

For anyone who’s interested in artificial intelligence and the effects it may have on urban life, see my Sept. 27, 2016 posting featuring the ‘One Hundred Year Study on Artificial Intelligence (AI100)’, hosted by Stanford University.

Points to anyone who recognized Jonah (Jonathan) Nolan as the producer for the US television series, Person of Interest, a programme based on the concept of a supercomputer with intelligence and personality and the ability to continuously monitor the population 24/7.

A dress that lights up according to reactions on Twitter

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I don’t usually have an opportunity to write about red carpet events but the recent Met Gala, also known as the Costume Institute Gala and the Met Ball, which took place on the evening of May 2, 2016 in New York, featured a ‘cognitive’ dress. Here’s more from a May 2, 2016 article by Emma Spedding for The Telegraph (UK),

“Tech white tie” was the dress code for last night’s Met Gala, inspired by the theme of this year’s Met fashion exhibition, ‘Manus x Machina: Fashion in the Age of Technology’. While many of the a-list attendees interpreted this to mean ‘silver sequins’, several rose to the challenge with beautiful, future-gazing gowns which give a glimpse of how our clothes might behave in the future.

Supermodel Karolina Kurkova wore a ‘cognitive’ Marchesa gown that was created in collaboration with technology company IBM. The two companies came together following a survey conducted by IBM which found that Marchesa was one of the favourite designers of its employees. The dress is created using a conductive fabric chosen from 40,000 options and embedded with 150 LED lights which change colour in reaction to the sentiments of Kurkova’s Twitter followers.

A May 2, 2016 article by Rose Pastore for Fast Company provides a little more technical detail and some insight into why Marchesa partnered with IBM,

At the Met Gala in Manhattan tonight [May 2, 2016], one model will be wearing a “cognitive dress”: A gown, designed by fashion house Marchesa, that will shift in color based on input from IBM’s Watson supercomputer. The dress features gauzy white roses, each embedded with an LED that will display different colors depending on the general sentiment of tweets about the Met Gala. The algorithm powering the dress relies on Watson Color Theory, which links emotions to colors, and on the Watson Tone Analyzer, a service that can detect emotion in text.

In addition to the color-changing cognitive dress, Marchesa designers are using Watson to get new color palette ideas. The designers choose from a list of emotions and concepts—things like romance, excitement, and power—and Watson recommends a palette of colors it associates with those sentiments.

An April 29, 2016 posting by Ann Rubin for IBM’s Think blog discusses the history of technology/art partnerships and provides more technical detail (yes!) about this one,

Throughout history, we’ve seen traces of technology enabling humans to create – from Da Vinci’s use of the camera obscura to Caravaggio’s work with mirrors and lenses. Today, cognitive systems like Watson are giving artists, designers and creative minds the tools to make sense of the world in ground-breaking ways, opening up new avenues for humans to approach creative thinking.

…

The dress’ cognitive creation relies on a mix of Watson APIs, cognitive tools from IBM Research, solutions from Watson developer partner Inno360 and the creative vision from the Marchesa design team. In advance of it making its exciting debut on the red carpet, we’d like to take you on the journey of how man and machine collaborated to create this special dress.

Rooted in the belief that color and images can indicate moods and send messages, Marchesa first selected five key human emotions – joy, passion, excitement, encouragement and curiosity – that they wanted the dress to convey. IBM Research then fed this data into the cognitive color design tool, a groundbreaking project out of IBM Research-Yorktown that understands the psychological effects of colors, the interrelationships between emotions, and image aesthetics.

This process also involved feeding Watson hundreds of images associated with Marchesa dresses in order to understand and learn the brand’s color palette. Ultimately, Watson was able to suggest color palettes that were in line with Marchesa’s brand and the identified emotions, which will come to life on the dress during the Met Gala.

Once the colors were finalized, Marchesa turned to IBM partner Inno360 to source a fabric for their creation. Using Inno360’s R&D platform – powered by a combination of seven Watson services – the team searched more than 40,000 sources for fabric information, narrowing down to 150 sources of the most useful options to consider for the dress.

From this selection, Inno360 worked in partnership with IBM Research-Almaden to identify printed and woven textiles that would respond well to the LED technology needed to execute the final part of the collaboration. Inno360 was then able to deliver 35 unique fabric recommendations based on a variety of criteria important to Marchesa, like weight, luminosity, and flexibility. From there, Marchesa weighed the benefits of different material compositions, weights and qualities to select the final fabric that suited the criteria for their dress and remained true to their brand.

Here’s what the dress looks like,

Courtesy of Marchesa Facebook page {https://www.facebook.com/MarchesaFashion/)

Watson is an artificial intelligence program,which I have written about a few times but I think this Feb. 28, 2011 posting (scroll down about 50% of the way), which mentions Watson, product placement, Jeopardy (tv quiz show), and medical diagnoses seems the most à propos given IBM’s latest product placement at the Met Gala.

Not the only ‘tech’ dress

There was at least one other ‘tech’ dress at the 2016 Met Gala, this one designed by Zac Posen and worn by Claire Danes. It did not receive a stellar review in a May 3, 2016 posting by Elaine Lui on Laineygossip.com,

People are losing their goddamn minds over this dress, by Zac Posen. Because it lights up.

…

It’s bullsh-t.

This is a BULLSH-T DRESS.

It’s Cinderella with a lamp shoved underneath her skirt.

…

Here’s a video of Danes and her dress at the Met Gala,

A Sept. 10, 2015 news item in People magazine indicates that Posen’s a different version of a ‘tech’ dress was a collaboration with Google (Note: Links have been removed),

Designer Zac Posen lit up his 2015 New York Fashion Week kickoff show on Tuesday by debuting a gorgeous and tech-savvy coded LED dress that blinked in different, dazzling pre-programmed patterns down the runway.

…

In coordination with Google’s non-profit organization, Made with Code, which inspires girls to pursue careers in tech coding, Posen teamed up with 30 girls (all between the ages of 13 and 18), who attended the show, to introduce the flashy dress — which was designed by Posen and coded by the young women.

“This is the future of the industry: mixing craft, fashion and technology,” the 34-year-old designer told PEOPLE. “There’s a discrepancy in the coding field, hardly any women are at the forefront, and that’s a real shame. If we can entice young women through the allure of fashion, to get them learning this language, why not?”

..

Through a micro controller, the gown displays coded patterns in 500 LED lights that are set to match the blues and yellows of Posen’s new collection. The circuit was designed and physically built into Posen’s dress fabric by 22-year-old up-and-coming fashion designer and computer science enthusiast, Maddy Maxey, who tells PEOPLE she was nervous watching Rocha [model Coco Rocha] make her way down the catwalk.

“It’s exactly as if she was carrying a microwave down the runway,” Maxey said. “It’s an entire circuit on a textile, so if one connection had come lose, the dress wouldn’t have worked. But, it did! And it was so deeply rewarding.”

Other ‘tech’ dresses

Back in 2009 I attended that year’s International Symposium on Electronic Arts and heard Clive van Heerden of Royal Philips Electronics talk about a number of innovative concepts including a ‘mood’ dress that would reveal the wearer’s emotions to whomever should glance their way. It was not a popular concept especially not in Japan where it was first tested.

The symposium also featured Maurits Waldemeyer who worked with fashion designer Chalayan Hussein and LED dresses and dresses that changed shape as the models went down the runway.

In 2010 there was a flurry of media interest in mood changing ‘smart’ clothes designed by researchers at Concordia University (Barbara Layne, Canada) and Goldsmiths College (Janis Jefferies, UK). Here’s more from a June 4, 2010 BBC news online item,

The clothes are connected to a database that analyses the data to work out a person’s emotional state.

Media, including songs, words and images, are then piped to the display and speakers in the clothes to calm a wearer or offer support.

Created as part of an artistic project called Wearable Absence the clothes are made from textiles woven with different sorts of wireless sensors. These can track a wide variety of tell-tale biological markers including temperature, heart rate, breathing and galvanic skin response.

Final comments

I don’t have anything grand to say. It is interesting to see the progression of ‘tech’ dresses from avant garde designers and academics to haute couture.

Engineering, entertainment, IBM’s Watson, and product placement

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A new partnership between the Entertainment Industries Council (EIC) and the US National Science Foundation (NSF) was announced last week. From the Feb. 25, 2011 news item on Nanowerk,

In honor of National Engineers Week, the Entertainment Industries Council, Inc. (EIC) and the National Science Foundation (NSF) have announced a new partnership to promote careers in science, engineering and technology. The partnership serves to enhance EIC’s ongoing Ready on the S.E.T. and … Action! program in collaboration with The Boeing Company, by providing additional expertise in science and technology to the entertainment industry creative community under the auspices of EIC’s First Draft brand.

I’m not familiar with the EIC or its ‘Ready on the S.E.T. and … Action!’ program but here’s a video featuring Pauley Perrette (from the US tv show NCIS) in one of the program’s public service announcements designed to encourage girls to enter the field of engineering,

This new program the ‘First Draft’ is a little different,

In addition to offering experts to writers, producers, directors, performers and creative executives on any and all areas of science, engineering and technology on-demand, the First Draft effort with NSF’s Science Scene program in the Office of Legislative and Public Affairs will also provide publications with depiction suggestions to creators, as well as conducting topic briefings. The first such briefing will take place in July, at the start of the television [tv] writing season. The half-day event, described as a sort-of “writer’s boot camp,” will offer up scientists and engineers in a variety of cutting-edge fields that may be useful to story development and technical guidance. Topics are expected to include such areas as nanotechnology, robotics and artificial intelligence, bioengineering (including artificial limbs and implants), forensics (including DNA analysis and miniaturized lab techniques), as well as artificial life and genetic engineering-and exciting tie-ins to aerospace engineering, among others.

If I read this correctly, they are running a workshop prior to any writing or production work being done. In other words, they’re getting to the writers and producers before the tv episodes are written or conceptualized. That means the usual order of writers and producers getting an idea for a story, finding an expert either to vet it from a technical/scientific perspective, and going into production is reversed. Now, the story idea will spring from the science and the technology. In a sense, you could say the ‘product placement’ (science and technology) drives the story or, alternatively, you could say it’s a neat piece of social engineering.

I’ve been thinking about social engineering especially on the heels of the ‘Watson’ computer triumph on Jeopardy, the tv quiz program, after three days (Feb. 14 – 16, 2011) of competing against humans (mentioned in my Feb. 14, 2011 posting). Shortly (Feb. 24, 2011) after Watson won, IBM (Watson’s creator) announced a collaboration with the University of Maryland’s School of Medicine on a project that could bring Watson into the examining room with you. From the article by Frank D. Roylance on physorg.com,

They have begun work on merging the speech recognition and question-answering skills of Watson – the computer that beat two humans on “Jeopardy!” last week – with the vast stores of clinical knowledge and analytical skills in the medical profession.

If it all works out, the end product could be a “Dr. Watson” in hospitals and physicians’ offices

“In the future, I see the software sitting with the physician as he is interviewing the patient, and processing information in real time, and correlating that with the patient’s medical record and other records,” said Dr. Eliot Siegel, director of the Maryland Imaging Research Technologies Lab at the University of Maryland School of Medicine in Baltimore.

Watson, he said, “has incredible potential to revolutionize how we interact with medical records; to be a really valuable assistant to me; to read all the literature pertinent to my practice … to always be at my side and help suggest problems, things in the medical records I need to know about; to suggest diagnoses and treatment options I may not have considered,” he said.

I found the timing interesting. First Watson demonstrates that it can think (it beat humans on a quiz that requires some semantic sophistication) in a fairly non-threatening way (the mistakes the computer made were odd, not like humans at all and therefore funny). Then within one week or so, an announcement is made about using Watson (some day) in the doctor’s office.

IBM made much of the fact that the computer was named after the company founder, Paul Watson, and not Sherlock Holmes’s Dr. Watson. Still, I’m sure if the company founder’s name had been Zloklikovits or another name considered challenging for one reason or another, they wouldn’t have used the company founder’s name.

I’m pointing out that there’s a great deal of planning and money on the line and it’s a good idea to be critical (i.e. not accept unthinkingly) of our entertainment from time to time.

Intelligence, computers, and robots

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Starting tonight, Feb. 14, 2011, you’ll be able to watch a computer compete against two former champions on the US television quiz programme, Jeopardy. The match between the IBM computer, named Watson, and the most accomplished champions that have ever played on Jeopardy, Ken Jennings and Brad Rutter, has been four years in the making. From the article by Julie Beswald on physorg.com,

“Let’s finish, ‘Chicks Dig Me’,” intones the somewhat monotone, but not unpleasant, voice of Watson, IBM’s new supercomputer built to compete on the game show Jeopardy!

The audience chuckles in response to the machine-like voice and its all-too-human assertion. But fellow contestant Ken Jennings gets the last laugh as he buzzes in and garners $1,000.

This exchange is part of a January 13 practice round for the world’s first man vs. machine game show. Scheduled to air February 14-16, the match pits Watson against the two best Jeopardy! players of all time. Jennings holds the record for the most consecutive games won, at 74. The other contestant, Brad Rutter, has winnings totaling over $3.2 million.

On Feb. 9, 2011, PBS’s NOVA science program broadcast a documentary about Watson whose name is derived from the company founder, Paul Watson, and not Sherlock Holmes’s companion and biographer, Dr. Watson. Titled the Smartest Machine on Earth, the show highlighted Watson’s learning process and some of the principles behind artificial intelligence. PBS’s website is featuring a live blogging event of tonight’s and the Feb. 15 and 16 matches. From the website,

On Monday [Feb. 14, 2011], our bloggers will be Nico Schlaefer and Hideki Shima, two Ph.D. students at Carnegie Mellon University’s Language Technologies Institute who worked on the Watson project.

At the same time that the ‘Watson’ event was being publicized last week, another news item on artificial intelligence and learning was making the rounds. From a Feb. 9, 2011 article by Mark Ward on BBC News ,

Robots could soon have an equivalent of the internet and Wikipedia.

European scientists have embarked on a project to let robots share and store what they discover about the world.

Called RoboEarth it will be a place that robots can upload data to when they master a task, and ask for help in carrying out new ones.

Researchers behind it hope it will allow robots to come into service more quickly, armed with a growing library of knowledge about their human masters. [emphasis mine]

You can read a first person account of the RoboEarth project on the IEEE (Institute of Electrical and Electronics Engineering) Spectrum’s Automaton Robotics blog in a posting by Markus Waibel,

As part of the European project RoboEarth, I am currently one of about 30 people working towards building an Internet for robots: a worldwide, open-source platform that allows any robot with a network connection to generate, share, and reuse data. The project is set up to deliver a proof of concept to show two things:

* RoboEarth greatly speeds up robot learning and adaptation in complex tasks.

* Robots using RoboEarth can execute tasks that were not explicitly planned for at design time.

The vision behind RoboEarth is much larger: Allow robots to encode, exchange, and reuse knowledge to help each other accomplish complex tasks. This goes beyond merely allowing robots to communicate via the Internet, outsourcing computation to the cloud, or linked data.

But before you yell “Skynet!,” think again. While the most similar things science fiction writers have imagined may well be the artificial intelligences in Terminator, the Space Odyssey series, or the Ender saga, I think those analogies are flawed. [emphasis mine] RoboEarth is about building a knowledge base, and while it may include intelligent web services or a robot app store, it will probably be about as self-aware as Wikipedia.

That said, my colleagues and I believe that if robots are to move out of the factories and work alongside humans, they will need to systematically share data and build on each other’s experience.

Unfortunately, Markus Waibel doesn’t explain why he thinks the analogies are flawed but he does lay out the reasoning for why robots should share information. For a more approachable and much briefer account, you can check out Ariel Schwartz’s Feb. 10, 2011 article on the Fast Company website,

The EU-funded [European Union] RoboEarth project is bringing together European scientists to build a network and database repository for robots to share information about the world. They will, if all goes as planned, use the network to store and retrieve information about objects, locations (including maps), and instructions about completing activities. Robots will be both the contributors and the editors of the repository.

…

With RoboEarth, one robot’s learning experiences are never lost–the data is passed on for other robots to mine. As RedOrbit explains, that means one robot’s experiences with, say, setting a dining room table could be passed on to others, so the butler robot of the future might know how to prepare for dinner guests without any prior programming.

There is a RoboEarth website, so we humans can get more information and hopefully keep up with the robots.

Happily and as there is with increasing frequency, there’s a Youtube video. This one features a robot downloading information from RoboEarth and using that information in a quasi hospital setting,

I find this use of popular entertainment, particularly obvious with Watson, to communicate about scientific advances quite interesting. On this same theme of popular culture as a means of science communication, I featured a Lady Gaga parody by a lab working on Alzheimer’s in my Jan. 28, 2011 posting. I also find the reference to “human masters” in the BBC article along with Waibel’s flat assertion that some science fiction analogies about artificial intelligence are flawed indicative of some very old anxieties as expressed in Mary Shelley’s Frankenstein.

ETA Feb. 14, 2011: The latest posting on the Pasco Phronesis blog, I, For One, Welcome Our Robot Game Show Overlords, features another opinion about the Watson appearances on Jeopardy. From the posting,

What will this mean? Given that a cursory search suggests opinion is divided on whether Watson will win this week, I have no idea. While it will likely be entertaining, and does represent a significant step forward in computing capabilities, I can’t help but think about the supercomputing race that makes waves only when a new computational record is made. It’s nice, and might prompt government action should they lose the number one standing. But what does it mean? What new outcomes do we have because of this? The conversation is rarely about what, to me, seems more important.