Experts are warning foragers to avoid using Google Images to identify mushrooms after the search engine is delivering misleading AI-generated results. Searches for a number of common edible mushrooms return wildly inaccurate images as the top result, despite these images being flagged as AI-generated. Foraging experts warn this could lead to dangerous, if not deadly, errors for foragers trying to identify safe mushrooms to eat. Professor David Hawksworth, a mycologist from the University of Southampton, told MailOnline: 'This is potentially extremely dangerous.' However, experts routinely warn that it isn't safe to pick up and eat mushrooms that we find on the ground - even if we think we can tell a safe species apart from a dangerous one.

The string of Autopilot crashes reveals the consequences of allowing a rapidly evolving technology to operate on the nation's roadways without significant government oversight, experts say. While NHTSA has several ongoing investigations into the company and specific crashes, critics argue the agency's approach is too reactive and has allowed a flawed technology to put Tesla drivers -- and those around them -- at risk. The approach contrasts with federal regulation of planes and railroads, where crashes involving new technology or equipment -- such as recurring issues with Boeing's 737 Max -- have resulted in sweeping action by agencies or Congress to ground planes or mandate new safety systems. Unlike planes, which are certified for airworthiness through a process called "type certification," passenger car models are not prescreened, but are subject to a set of regulations called Federal Motor Vehicle Safety Standards, which manufacturers face the burden to meet.

Imagine you are in a foreign country where you don't speak the language and your small child unexpectedly starts to have a fever seizure. You take them to the hospital, and the doctors use an online translator to let you know that your kid is going to be OK. But "your child is having a seizure" accidentally comes up in your mother tongue is "your child is dead." This specific example is a very real possibility, according to a 2014 study published in the British Medical Journal about the limited usefulness of AI-powered machine translation in communications between patients and doctors. Sometimes we need American-British translation, too.)

In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands. In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity--acting only on desired or targeted cells or neuroreceptors, for instance--and low toxicity to reduce ill effects.

A new form of algorithm is moving into the world, which has the capability to rewrite bits of its own code. The 18th of March 2018 was the day tech insiders had been dreading. That night, a new moon added almost no light to a poorly lit four-lane road in Tempe, AZ, as a specially adapted Uber Volvo XC90 detected an object ahead. Part of the modern gold rush to develop self-driving vehicles, the SUV had been driving autonomously, with no input from its human backup driver, for 19 minutes. An array of radar and light-emitting lidar sensors allowed onboard algorithms to calculate that, given their host vehicle's steady speed of 43mph, the object was six seconds away--assuming it remained stationary.

The 18th of March, 2018, was the day tech insiders had been dreading. That night, a new moon added almost no light to a poorly lit four-lane road in Tempe, Arizona, as a specially adapted Uber Volvo XC90 detected an object ahead. Part of the modern gold rush to develop self-driving vehicles, the SUV had been driving autonomously, with no input from its human backup driver, for 19 minutes. An array of radar and light-emitting lidar sensors allowed onboard algorithms to calculate that, given their host vehicle's steady speed of 43mph, the object was six seconds away – assuming it remained stationary. But objects in roads seldom remain stationary, so more algorithms crawled a database of recognizable mechanical and biological entities, searching for a fit from which this one's likely behavior could be inferred. At first the computer drew a blank; seconds later, it decided it was dealing with another car, expecting it to drive away and require no special action. Only at the last second was a clear identification found – a woman with a bike, shopping bags hanging confusingly from handlebars, doubtless assuming the Volvo would route around her as any ordinary vehicle would. Barred from taking evasive action on its own, the computer abruptly handed control back to its human master, but the master wasn't paying attention. Elaine Herzberg, aged 49, was struck and killed, leaving more reflective members of the tech community with two uncomfortable questions: was this algorithmic tragedy inevitable? And how used to such incidents would we, should we, be prepared to get? "In some ways we've lost agency. When programs pass into code and code passes into algorithms and then algorithms start to create new algorithms, it gets farther and farther from human agency. Software is released into a code universe which no one can fully understand."