AI to spot wildfires, human oversight of AI, and more!

Last Week in AI #121

Mini Briefs

AI Could Spot Wildfires Faster Than Humans

Tower-mounted cameras have assisted California communities in spotting wildfires for years. However, it is very difficult for human operators to keep up with a wall of live video feeds 24/7 to monitor potential flareups. Since May this year, Sonoma County, where the destructive Tubbs Fire in 2017 occurred, have been experimenting with AI software to process these videos in real time and look for hotspots. Early results are mixed - sometimes the AI system can raise alerts faster than human operators, sometimes slower. Beyond Sonoma, AI-assisted wildfire monitoring is slowly being adopted across the western U.S. These systems will get better over time as more data is collected per location - the algorithm needs to be finetuned to specific weather patterns on site. In the future, many hope that AI systems can also predict likely spots for fires before they occur by accessing live sensor data beyond cameras, such as air temperature and soil moisture.

The False Comfort of Human Oversight as an Antidote to A.I. Harm

Recently, policy makers have called for greater human oversight on AI applications in industry to reduce harm. However, effective implementation of such oversight is challenging, and there are several common pitfalls. The presence of a human in a larger decision making process does not automatically make the decisions produce less harm. For example, in many cases it was found that humans overestimate the credibility of AI systems and would simply "rubber stamp" automated decisions. The presence of human operators also make it easier for institutions to both legitimize automated decisions and also shift responsibility onto the humans, instead of the AI system, when harms occur. This all underpins a seeming paradox with AI decision making, that they are supposed to "improve upon the cognitive limits and biases of humans" and yet humans are being presented as "the essential backstop overseeing algorithmic limits and biases."

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  • There's More To Machine Learning Than CNNs - "Neural networks - and convolutional neural networks (CNNs) in particular - have received an abundance of attention over the last few years, but they're not the only useful machine-learning structures."

  • Fun and Dystopia With AI-Based Code Generation Using GPT-J-6B - "Since OpenAI will not open-source the 175 billion parameter GPT-3 text generation model, others such as EleutherAI are developing their own, by training not-quite-as-large Transformer-based models but still getting impressive results."


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