Comment: In competition, people get discouraged by competent robots

After each round, participants filled out a questionnaire rating the robot’s competence, their own competence and the robot’s likability. The researchers found that as the robot performed better, people rated its competence higher, its likability lower and their own competence lower.

Lefkowitz, M. (2019). In competition, people get discouraged by competent robots. Cornell Chronicle.

This is worth noting since it seems increasingly likely that we’ll soon be working, not only with more competent robots but also with more competent software. There are already concerns around how clinicians will respond to the recommendations of clinical decision-support systems, especially when those systems make suggestions that are at odds with the clinician’s intuition.

Paradoxically, the effect may be even worse with expert clinicians who may not always be able to explain their decision-making. Novices, who use more analytical frameworks (or even basic algorithms like, IF this, THEN that) may find it easier to modify their decisions because their reasoning is more “visible” (System 2). Experts, who rely more on subconscious pattern recognition (System 1), may be less able to identify where in their reasoning process they were victim to confounders like confirmation or availability bia, and so less likely to modify their decisions.

It seems really clear that we need to start thinking about how we’re going to prepare current and future clinicians for the arrival of intelligent agents in the clinical context. If we start disregarding the recommendations of clinical decision support systems, not because they produce errors in judgement but because we simply don’t like them, then there’s a strong case to be made that it is the human that we cannot trust.


Contrast this with automation bias, which is the tendency to give more credence to decisions made by machines because of a misplaced notion that algorithms are simply more trustworthy than people.

Algorithms are not robots

We should stop using images of humanoid robots to represent an embodied form of artificial intelligence, especially when the AI being referenced is an algorithm, which in almost all cases in the mainstream media, it is. It’s confusing for readers because we’re nowhere near the kind of general intelligence that these pictures imply. For the foreseeable future, “AI” is a set of machine learning algorithms that “maximise a reward function” and is incapable of anything more than solving very specific problems with a lot of help.

AI isn’t magic, it’s just maths. I know that statistical methods aren’t as cool as the androids but if we really want people to get a better conceptual understanding of AI we’d be better off using images like this to illustrate the outputs of AI-based systems:

Robots in the classroom? Preparing for the automation of teaching | BERA

Agendas around AI and education have been dominated by technology designers and vendors, business interests and corporate reformers. There is a clear need for vigorous responses from educators, students, parents and other groups with a stake in public education. What do we all want from our education systems as AI-driven automation becomes more prominent across society?

Source: Robots in the classroom? Preparing for the automation of teaching | BERA

We need teachers, clinicians, and clinician educators involved in the process of designing, developing, implementing and evaluating AI-based systems in the higher education and clinical context. As long as the agenda for 21st century education and clinical care is driven by corporate interests (and how could it not, given the enormous commercial value of AI), it’s likely that those responsible for teaching the next generation of health professionals will be passive recipients of algorithmic decision-making rather than empowered participants in their design.

I enjoyed reading (January)

This post is also a bit delayed, but I’m OK with that. During January I found myself reading a bit more than usual about robots, androids, augmented reality and related topics. I’m not sure why it worked out that way, but this collection is more or less representative of what I found interesting during that time. Interestingly, I realised that a common thread throughout this theme are that they’re pretty much related to three books by Daniel Suarez; Daemon, Freedom, and Kill Decision. If you enjoy this kind of thing, you have to read them.

I, Glasshole: My Year With Google Glass (Mat Honan): I’m fascinated with the concept of wearable, context-aware devices and services, of which Glass is simply the most well-known. I think that the ability to overlay digital information on top of the reality we perceive represents an astounding change in how we experience the world.

For much of 2013, I wore the future across my brow, a true Glasshole peering uncertainly into the post-screen world. I’m not out here all alone, at least not for long. The future is coming to your face too. And your wrist. Hell, it might even be in your clothes. You’re going to be wearing the future all over yourself, and soon. When it comes to wearable computing, it’s no longer a question of if it happens, only when and why and can you get in front of it to stop it with a ball-pein hammer? (Answers: Soon. Because it is incredibly convenient. Probably not.) In a few years, we might all be Glassholes. But in 2013, maybe for the last time, I was in dubiously exclusive face-computing company.

Robots of death, robots of love: The reality of android soldiers and why laws for robots are doomed to failure (Steve Ranger): The idea of fully autonomous robots that are able to make decisions in critical situations is both disturbing and appealing to me. Disturbing because embedding a moral framework that can deal with the complexity of warfare is ethically problematic. Appealing because in many situations, robots may actually be able to make better decisions than human beings (think of self-driving cars).

While fully autonomous robot weapons might not be deployed for two or three decades, the International Committee for Robot Arms Control (ICRAC), an international group of academics and experts concerned about the implications of a robot arms race, argues a prohibition on the development and deployment of autonomous weapons systems is the correct approach. “Machines should not be allowed to make the decision to kill people,” it states.

Better Than Human: Why Robots Will — And Must — Take Our Jobs (Kevin Kelly): Kevin Kelly’s article, We are the web, was one of the first things I read that profoundly changed the way I think about the internet. Needless to say, I almost always find his thoughts on technology to be insightful and thought-provoking.

All the while, robots will continue their migration into white-collar work. We already have artificial intelligence in many of our machines; we just don’t call it that. Witness one piece of software by Narrative Science (profiled in issue 20.05) that can write newspaper stories about sports games directly from the games’ stats or generate a synopsis of a company’s stock performance each day from bits of text around the web. Any job dealing with reams of paperwork will be taken over by bots, including much of medicine. Even those areas of medicine not defined by paperwork, such as surgery, are becoming increasingly robotic. The rote tasks of any information-intensive job can be automated. It doesn’t matter if you are a doctor, lawyer, architect, reporter, or even programmer: The robot takeover will be epic.

And it has already begun.

A review of Her (Ray Kurzweil): Kurweil’s thinking on the merging of human beings with technology is fascinating. If you’re interested in this topic, the collection of essays on his blog is awesome.

With emerging eye-mounted displays that project images onto the wearer’s retinas and also look out at the world, we will indeed soon be able to do exactly that. When we send nanobots into the brain — a circa-2030s scenario by my timeline — we will be able to do this with all of the senses, and even intercept other people’s emotional responses.