Tag: machine learning
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Podcast: The trouble with AI
https://samharris.org/episode/SE5DD11091B Sam Harris speaks with Stuart Russell and Gary Marcus about recent developments in artificial intelligence and the long-term risks of producing artificial general intelligence (AGI). They discuss the limitations of Deep Learning, the surprising power of narrow AI, ChatGPT, a possible misinformation apocalypse, the problem of instantiating human values, the business model of the…
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Bring on the algorithmic scrutiny of academic work
I’m reviewing a grant application and it’s been… hard. I feel reasonably confident that I can quickly get my head around a research project but sometimes the writing is so poor that I have to read some passages 5 times before (I think) I understand what’s going on. So I was delighted to find explainjargon.com,…
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People-centred AI – Application
Sometime in 2021 I put together a short video describing my thinking around the relationship between human beings and the development of artificial intelligence. The video was part of an unsuccessful application but I thought it might still be interesting enough to share here. The video describes some of the ways in which I see…
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I was on the Man & Machine podcast last week
Last week I had a conversation with Ean Bett of the Man & Machine podcast, which we recorded and published. I had a great time talking to Ean about some of the progress we see taking place in clinical AI.
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On the poor performance of AI models during the pandemic
Heaven, W.D. (2021). Hundreds of AI tools have been built to catch covid. None of them helped. MIT Technology Review. In the end, many hundreds of predictive tools were developed. None of them made a real difference, and some were potentially harmful. That’s the damning conclusion of multiple studies published in the last few months.…
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AI is already an important part of clinical practice. Just not in the way that you think.
We’re all using AI all the time. We just don’t always recognise it. There’s a lot of discussion around the introduction of AI-based systems into clinical practice and healthcare systems. But these discussions tend to focus on the systems that are being designed, developed, and deployed as part of formal processes centred on ‘big ideas’…
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Seeing beyond our own paradigms
Yesterday I saw this tweet from Enrico Coiera: So I downloaded the editorial and noted these sections: Through the Internet, the public has access to a growing supply of information on health and disease, often of variable quality and relevance. As a result, providing information on health will no longer be the exclusive remit of…
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Podcast: Clinicians’ ‘Number-One Wish’ for Artificial Intelligence
…we installed cheap depth sensors that can collect human behavior data on patients and clinicians without infringing on their privacy, because these are not photo grabs of people’s faces and identities. With that information, we can observe longitudinally, 24/7, whether proper care is being given to our patients and provide feedback in the health delivery…
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Why I think that AI-based grading in education is inevitable.
A few days ago I commented on an article that discusses the introduction of AI into education and why teachers shouldn’t worry about it. I also said that AI for grading was inevitable because it would be cheaper, and more reliable, fair and valid than human beings. I got some pushback from Ben on Twitter…
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The Last Mile: Where Artificial Intelligence Meets Reality
Coiera, E. (2019). The Last Mile: Where Artificial Intelligence Meets Reality. Journal of Medical Internet Research, 21(11), e16323. https://doi.org/10.2196/16323 “…implementation should be seen as an agile, iterative, and lightweight process of obtaining training data, developing algorithms, and crafting these into tools and workflows.” A short article (2 pages of text) describing the challenges of building…
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Resource: Elements of AI course.
The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory…
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Don’t blame biased algorithms for outcomes you don’t like.
“What algorithms are doing is giving you a look in the mirror. They reflect the inequalities of our society.” Sandra Wachter, in The Week in Tech: Algorithmic Bias Is Bad. Uncovering It Is Good. Cordliffe, J. (2019). The New York Times. We can start by agreeing that algorithms are biased. Unfortunately, this is where most…
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UCT seminar: Shaping our algorithms
Tomorrow I’ll be presenting a short seminar at the University of Cape Town on a book chapter that was published earlier this year, called Shaping our algorithms before they shape us. Here are the slides I’ll be using, which I think are a useful summary of the chapter itself.
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Book chapter published: Shaping our algorithms before they shape us
I’ve just had a chapter published in an edited collection entitled: Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices. The book is edited by Jeremy Knox, Yuchen Wang and Michael Gallagher and is available here. Here’s the citation: Rowe M. (2019) Shaping Our Algorithms Before They Shape Us. In: Knox J., Wang Y.,…
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Research project exploring clinicians’ perspectives of the introduction of ML into clinical practice
I recently received ethics clearance to begin an explorative study looking at how physiotherapists think about the introduction of machine learning into clinical practice. The study will use an international survey and a series of interviews to gather data on clinicians’ perspectives on questions like the following: What aspects of clinical practice are vulnerable to…
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Article published – An introduction to machine learning for clinicians
It’s a nice coincidence that my article on machine learning for clinicians has been published at around the same time that my poster on a similar topic was presented at WCPT. I’m quite happy with this paper and think it offers a useful overview of the topic of machine learning that is specific to clinical…
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WCPT poster: Introduction to machine learning in healthcare
My poster and list of references for the WCPT 2019 conference in Geneva.
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Algorithmic de-skilling of clinical decision-makers
What will we do when we don’t drive most of the time but have a car that hands control to us during an extreme event? Agrawal, A., Gans, J. & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Before I get to the takehome message, I need to set this up a…
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First compute no harm
Is it acceptable for algorithms today, or an AGI in a decade’s time, to suggest withdrawal of aggressive care and so hasten death? Or alternatively, should it recommend persistence with futile care? The notion of “doing no harm” is stretched further when an AI must choose between patient and societal benefit. We thus need to…