Will human therapists go the way of the Dodo?

ai therapist

An increasing number of patients are using technology for a quick fix. Photographed by Mikael Jansson, Vogue, March 2016

PL  – So, here’s an informative piece on a person’s experience using an on-demand interactive video therapist, as compared to her human therapist. In Vogue Magazine, no less. A sign this is quickly becoming trendy. But is it effective?

In the first paragraph, the author of the article identifies the limitations of her digital therapist:

“I wish I could ask (she eventually named her digital therapist Raph) to consider making an exception, but he and I aren’t in the habit of discussing my problems

But the author also recognizes the unique value of the digital therapist as she reflects on past sessions with her human therapist:

“I saw an in-the-flesh therapist last year. Alice. She had a spot-on sense for when to probe and when to pass the tissues. I adored her. But I am perennially juggling numerous assignments, and committing to a regular weekly appointment is nearly impossible.”

Later on, when the author was faced with another crisis, she returned to her human therapist and this was her observation of that experience:

“she doesn’t offer advice or strategies so much as sympathy and support—comforting but short-lived. By evening I’m as worried as ever.”

On the other hand, this is her view of her digital therapist:

“Raph had actually come to the rescue in unexpected ways. His pragmatic MO is better suited to how I live now—protective of my time, enmeshed with technology. A few months after I first “met” Raph, my anxiety has significantly dropped”

This, of course, was a story written by a successful educated woman, working with an interactive video, who had experiences with a human therapist to draw upon for reference.

What about the effectiveness of a digital therapist for a more diverse population with social, economic and cultural differences?

It has already been shown that, done right, this kind of tech has great potential. In fact, as a more affordable option, it may do the most good for the wider population.

The ultimate goal for tech designers should be to create a more personalized experience. Instant and intimate. Tech that gets to know the person and their situation, individually. Available any time. Tech that can access additional electronic resources for the person in real-time, such as the above mentioned interactive video.  

But first, tech designers must address a core problem with mindset. They code for a rational world while therapists deal with irrational human beings. As a group, they believe they are working to create an omniscient intelligence that does not need to interact with the human to know the human. They believe it can do this by reading the human’s emails, watching their searches, where they go, what they buy, who they connect with, what they share, etc. As if that’s all humans are about. As if they can be statistically profiled and treated to predetermined multi-stepped programs.

This is an incompatible approach for humans and the human experience. Tech is a reflection of the perceptions of its coders. And coders, like doctors, have their limitations.

In her recent book, Just Medicine, Dayna Bowen Matthew highlights research that shows 83,570 minorities die each year from implicit bias from well-meaning doctors. This should be a cautionary warning. Digital therapists could soon have a reach and impact that far exceeds well-trained human doctors and therapists. A poor foundational design for AI could have devastating consequences for humans.

A wildcard was recently introduced with Google’s AlphaGo, an artificial intelligence that plays the board game Go. In a historic Go match between Lee Sedol, one of the world’s top players, AlphaGo won the match four out of five games. This was a surprising development. Many thought this level of achievement was 10 years out.  

The point: Artificial intelligence is progressing at an extraordinary pace, unexpected by most all the experts. It’s too exciting, too easy, too convenient. To say nothing of its potential to be “free,” when tech giants fully grasp the unparalleled personal data they can collect. The Jeanie (or Joker) is out of the bottle. And digital coaches are emerging. Capable of drawing upon and sorting vast amounts of digital data.

Meanwhile, the medical and behavioral fields are going too slow. Way too slow. 

They are losing ground (most likely have already lost) control of their future by vainly believing that a cache of PhDs, research and accreditations, CBT and other treatment protocols, government regulations and HIPPA, is beyond the challenge and reach of tech giants. Soon, very soon, therapists that deal in non-critical non-crisis issues could be bypassed when someone like Apple hangs up its ‘coaching’ shingle: “Siri is In.”

The most important breakthrough of all will be the seamless integration of a digital coach with human therapists, accessible upon immediate request, in collaborative and complementary roles.

This combined effort could vastly extend the reach and impact of all therapies for the sake of all human beings.

Source: Vogue

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

How To Teach Robots Right and Wrong

Artificial Moral Agents

Prof.-Nayef-Al-Rodhan_gallerylarge

Nayef Al-Rodhan

Over the years, robots have become smarter and more autonomous, but so far they still lack an essential feature: the capacity for moral reasoning. This limits their ability to make good decisions in complex situations.

The inevitable next step, therefore, would seem to be the design of artificial moral agents,” a term for intelligent systems endowed with moral reasoning that are able to interact with humans as partners. In contrast with software programs, which function as tools, artificial agents have various degrees of autonomy.

However, robot morality is not simply a binary variable. In their seminal work Moral Machines, Yale’s Wendell Wallach and Indiana University’s Colin Allen analyze different gradations of the ethical sensitivity of robots. They distinguish between operational morality and functional morality. Operational morality refers to situations and possible responses that have been entirely anticipated and precoded by the designer of the robot system. This could include the profiling of an enemy combatant by age or physical appearance.

The most critical of these dilemmas is the question of whose morality robots will inherit.

Functional morality involves robot responses to scenarios unanticipated by the programmer, where the robot will need some ability to make ethical decisions alone. Here, they write, robots are endowed with the capacity to assess and respond to “morally significant aspects of their own actions.” This is a much greater challenge.

The attempt to develop moral robots faces a host of technical obstacles, but, more important, it also opens a Pandora’s box of ethical dilemmas.

Moral values differ greatly from individual to individual, across national, religious, and ideological boundaries, and are highly dependent on contextEven within any single category, these values develop and evolve over time.

Uncertainty over which moral framework to choose underlies the difficulty and limitations of ascribing moral values to artificial systems … To implement either of these frameworks effectively, a robot would need to be equipped with an almost impossible amount of information. Even beyond the issue of a robot’s decision-making process, the specific issue of cultural relativism remains difficult to resolve: no one set of standards and guidelines for a robot’s choices exists.    

For the time being, most questions of relativism are being set aside for two reasons. First, the U.S. military remains the chief patron of artificial intelligence for military applications and Silicon Valley for other applications. As such, American interpretations of morality, with its emphasis on freedom and responsibility, will remain the default.

Source: Foreign Affairs The Moral Code, August 12, 2015

PL – EXCELLENT summary of a very complex, delicate but critical issue Professor Al-Rodhan!

In our work we propose an essential activity in the process of moralizing AI that is being overlooked. An approach that facilitates what you put so well, for “AI to interact with humans as partners.”

We question the possibility that binary-coded AI/logic-based AI, in its current form, will one day switch from amoral to moral. This would first require a universal agreement of what constitutes morals, and secondarily, it would require the successful upload/integration of morals or moral capacity into AI computing. 

We do think AI can be taught “culturally relevant” moral reasoning though, by implementing a new human/AI interface that includes a collaborative engagement protocol. A protocol that makes it possible for AI to interact with the person in a way that the AI learns what is culturally relevant to each person, individually. AI that learns the values/morals of the individual and then interacts with the individual based on what was learned.

We call this a “whole person” engagement protocol. This person-focused approach includes AI/human interaction that embraces quantum cognition as a way of understanding what appears to be human irrationality. [Behavior and choices of which, from a classical probability-based decision model, are judged to be irrational and cannot be computed.]

This whole person approach, has a different purpose, and can produce different outcomes, than current omniscient/clandestine-style methods of AI/human information-gathering that are more like spying then collaborating, since the human’s awareness of self and situation is not advanced, but rather, is only benefited as it relates to things to buy, places to go and schedules to meet. 

Visualization is a critical component for AI to engage the whole person. In this case, a visual that displays interlinking data for the human. That breaks through the limitations of human working memory by displaying complex data of a person/situation in context. That incorporates a human‘s most basic reliable two ways of know, big picture and details, that have to be kept in dialogue with one another. Which makes it possible for the person themselves to make meaning, decide and act, in real-time. [The value of visualization was demonstrated in 2013 in physics with the discovery of the Amplituhedron. It replaced 500 pages of algebra formulas in one simple visual, thus reducing overwhelm related to linear processing.]        

This kind of collaborative engagement between AI and humans (even groups of humans) sets the stage for AI to offer real-time personalized feedback for/about the individual or group. It can put the individual in the driver’s seat of his/her life as it relates to self and situation. It makes it possible for humans to navigate any kind of complex human situation such as, for instance, personal growth, relationships, child rearing, health, career, company issues, community issues, conflicts, etc … (In simpler terms, what we refer to as the “tough human stuff.”)

AI could then address human behavior, which, up to now, has been the elephant in the room for coders and AI developers.

We recognize that this model for AI / human interaction does not solve the ultimate AI morals/values dilemma. But it could serve to advance four major areas of this discussion:

  1. By feeding back morals/values data to individual humans, it could advance their own awareness more quickly. (The act of seeing complex contextual data expands consciousness for humans and makes it possible for them to shift and grow.)
  2. It would help humans help themselves right now (not 10 or 20 years from now).
  3. It would create a new class of data, perceptual data, as it relates to individual beliefs that drive human behavior.
  4. It would allow for AI to process this additional “perceptual” data, collectively over time, to become a form of “artificial moral agent” with enhanced “moral reasoning” “working in partnership with humans.

Click here to leave a comment at the end of this post

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

Irrational thinking mimics much of what we observe in quantum physics

Quantum Physics Explains Why You Suck at Making Decisions (but what about AI?)

We normally think of physics and psychology inhabiting two very distinct places in science, but when you realize they exist in the same universe, you start to see connections and find out how they can learn from one-another. Case in point: a pair of new studies by researchers at Ohio State University that argue how quantum physics can explain human irrationality and paradoxical thinking — and how this way of thinking can actually be of great benefit.

Conventional problem-solving and decision-making processes often lead on classical probability theory, which outlines how humans make their best choices based on evaluating the probability of good outcomes.

But according to Zheng Joyce Wang, a communications researcher who led both studies, choices that don’t line up with classical probability theory are often labeled “irrational.” Yet, “they’re consistent with quantum theory — and with how people really behave,” she says.

The two new papers suggest that seemingly-irrational thinking mimics much of what we observe in quantum physics, which we normally think of as extremely chaotic and almost hopelessly random.

Quantum-like behavior and choices don’t follow standard, logical processes and outcomes. But like quantum physics, quantum-like behavior and thinking, Wang argues, can help us to understand complex questions better.

Wang argues that before we make a choice, our options are all superpositioned. Each possibility adds a whole new layer of dimensions, making the decision process even more complicated. Under conventional approaches to psychology, the process makes no sense, but under a quantum approach, Wang argues that the decision-making process suddenly becomes clear.

Source: Inverse.com

PL – As noted in other posts on this site, AI is rational, based on logic and following rules. And that has its own complications. (see Google cars post.)

If humans, as these papers suggest, operate in a different space, mimicking much of quantum physics, the question we should be asking ourselves is: What would it take for average humans and machines to COLLABORATE in solution-finding? Particularly, about human behavior and growth — the “tough human stuff,” as we, the writers of this blog, have labeled it. 

Let’s not make this about one or the other. How can humans and machines benefit each other? Is there a way to bridge the divide? We propose there is. 

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail