Tag: self-driving cars
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Podcast: Nathan Labenz on AI breakthroughs
https://80000hours.org/podcast/episodes/nathan-labenz-ai-breakthroughs-controversies/ AI entrepreneur Nathan Labenz discusses the capabilities and limitations of AI, concerns about AI deception, breakthroughs in protein folding, safety comparison of self-driving cars, the potential of GPT for vision, the online conversation around AI safety, negative impact of Twitter on public discourse, contrasting views on AI, backfire of anti-regulation sentiment in tech industry,…
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Weekly digest (24-30 Apr 2023)
Modularisation of AI modelsI’m not even sure if this is a category, but I’ve been thinking about modularisation in the AI ecosystem. Basically, where you have component parts that are chained together to achieve objectives that no single component can achieve independently. When OpenAI enabled plugins for ChatGPT they extended the functionality of their language…
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Comment: There’s a new obstacle to getting a job after college: Getting approved by AI
Companies may not be ready to outsource vetting candidates for C-Suite and executive positions to algorithms, but the stakes are lower for entry-level roles and internships. That means some of today’s college students are effectively the guinea pigs for a largely unproven mechanism for evaluating applicants. Metz, R. (2019). There’s a new obstacle to getting…
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Comment: Self-driving Mercedes will be programmed to sacrifice pedestrians to save the driver.
As we dig deeper, it seems that the problems faced by driverless cars and by human drivers are much the same. We try to avoid crashes and collisions, and we have to make split-second decisions when we can’t. Those decisions are governed by our programming and experience. The differences are that computers can think a…
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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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Prof Allan Dafoe on trying to prepare the world for the possibility that AI will destabilise global politics
…even if we stopped at today’s AI technology and simply collected more data, built more sensors, and added more computing capacity, extreme systemic risks could emerge, including: 1) Mass labor displacement, unemployment, and inequality; 2)The rise of a more oligopolistic global market structure, potentially moving us away from our liberal economic world order; 3)Imagery intelligence…
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Defensive Diagnostics: the legal implications of AI in radiology
Doctors are human. And humans make mistakes. And while scientific advancements have dramatically improved our ability to detect and treat illness, they have also engendered a perception of precision, exactness and infallibility. When patient expectations collide with human error, malpractice lawsuits are born. And it’s a very expensive problem. Source: Defensive Diagnostics: the legal implications…
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The first AI disruption in medicine might not be radiology
Over 90% of traffic accidents are caused by human error. Whether it is drink driving, inattention, speeding, straight up bad driving, or any other of a myriad of reasons why people crash their cars, the fact is humans are really dangerous on the road. In the USA we average an accident every 200,000 to 500,000…
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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…