This paper summarizes and evaluates various approaches, methods, and techniques for pursuing fairness in artificial intelligence (AI) systems. It examines the merits and shortcomings of these measures and proposes practical guidelines for defining, measuring, and preventing bias in AI. In particular, it cautions against some of the simplistic, yet common, methods for evaluating bias in AI systems, and offers more sophisticated and effective alternatives. The paper also addresses widespread controversies and confusions in the field by providing a common language among different stakeholders of high-impact AI systems. It describes various trade-offs involving AI fairness, and provides practical recommendations for balancing them. It offers techniques for evaluating the costs and benefits of fairness targets, and defines the role of human judgment in setting these targets. This paper provides discussions and guidelines for AI practitioners, organization leaders, and policymakers, as well as various links to additional materials for a more technical audience. Numerous real-world examples are provided to clarify the concepts, challenges, and recommendations from a practical perspective.

Scientists have developed a new machine-learning platform that makes the algorithms that control particle beams and lasers smarter than ever before. Their work could help lead to the development of new and improved particle accelerators that will help scientists unlock the secrets of the subatomic world. Daniele Filippetto and colleagues at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) developed the setup to automatically compensate for real-time changes to accelerator beams and other components, such as magnets. Their machine learning approach is also better than contemporary beam control systems at both understanding why things fail, and then using physics to formulate a response. A paper describing the research was published late last year in Nature Scientific Reports.

Researchers at the University of Central Florida have created AI technology that mimics the human eye. The technology might result in highly developed artificial intelligence that can instantaneously understand what it sees and has uses in robotics and self-driving cars. Researchers at the University of Central Florida (UCF) have built a device for artificial intelligence that replicates the retina of the eye. The research might result in cutting-edge AI that can identify what it sees right away, such as automated descriptions of photos captured with a camera or a phone. The technology could also be used in robots and self-driving vehicles.

A 48-year-old patient in New York City who is unable to move and speak due to severe paralysis from ALS became the first to receive a permanent brain implant that could allow him to communicate telepathically - a milestone for Synchron, the startup behind the technology, which beat Elon Musk's Neuralink to the punch with its advance. The procedure took place July 6 at Mount Sinai West medical center in Manhattan, where a 1.5-inch long implant - a brain-computer interface (BCI) as a stentrode - made of wires and electrodes was implanted into the patient's brain without the need for cutting into their skull or damaging tissue. 'The first-in-human implant of an endovascular BCI in the U.S. is a major clinical milestone that opens up new possibilities for patients with paralysis,' said Dr. Tom Oxley, CEO & Founder of Synchron, in a statement. 'The first-in-human implant of an endovascular BCI in the U.S. is a major clinical milestone that opens up new possibilities for patients with paralysis,' said Dr. Tom Oxley, CEO & Founder of Synchron, in a statement. 'Our technology is for the millions of people who have lost the ability to use their hands to control digital devices.

Britain is to start testing Star Wars-style laser weapons that will be able to shoot down drones and rockets from up to six miles away. Defence company Raytheon UK has announced it will be opening an advanced laser integration centre in Livingston, West Lothian next year. It said the new European hub will focus on'testing, fielding and maintenance of defensive high-energy laser (HEL) weapons'. The weapons will be designed to take down drones, rockets, artillery and mortars with just a highly concentrated beam of light. Raytheon UK was given a demonstrator contract to deliver an HEL weapon system to the UK Ministry of Defence (MOD) last September.

Brain-computer interfaces have become a practical (if limited) reality in the US. Synchron says it has become the first in the country to implant a BCI in a human patient. Doctors in New York's Mount Sinai West implanted the company's Stentrode in the motor cortex of a participant in Synchron's COMMAND trial, which aims to gauge the usefulness and safety of BCIs for providing hands-free device control to people with severe paralysis. Ideally, technology like Stentrode will offer independence to people who want to email, text and otherwise handle digital tasks that others take for granted. Surgeons installed the implant using an endovascular procedure that avoids the intrusiveness of open-brain surgery by going through the jugular vein.

The CEO of Turkey's Baykar, which makes the drones being widely used by Ukraine against Russian forces, has ruled out supplying the Bayraktar TB2 to Moscow. In an interview with CNN on Monday, Haluk Bayraktar said Ukraine is "under very heavy aggression and disproportionate attacks". When pressed by CNN presenter Julia Chatterley, who repeatedly asked, "Would you supply Russia?", Bayraktar responded: "We have not delivered or supplied them with anything, [and] we will as well never do such a thing because we support Ukraine, support its sovereignty, its resistance for its independence." Bayraktar said he is proud that Bayraktar TB2 has become one of the symbols of the Ukrainian resistance against Russia. "It's very touching," he said, hailing "years of cooperation" and "strong bonds" with Ukraine.

The UK Government has put forward proposals on the future regulation of AI, which would see various regulators apply six'principles' to markets which are implementing such technologies. The Government has sketched out its approach to regulating AI in a paper published today, which describes'proposed rules addressing future risks and opportunities so businesses are clear how they can develop and use AI systems and consumers are confident they are safe and robust.' It has come up with six core principles that regulators in different sectors would have to enforce, which are claims are designed to focus on supporting growth and avoiding'unnecessary barriers being placed on businesses'. Some of the applications around these rules could be about sharing information as to how businesses test AI reliability, and how any related deployments are'safe and avoid unfair bias.' Emphasis is placed on having different bodies enforce things relevant to their sectors, as opposed to what it describes as a more centralised way of keeping an eye on AI coming out of the EU – so Ofcom, the Competition and Markets Authority, the Information Commissioner's Office, the Financial Conduct Authority and the Medicine and Healthcare Products Regulatory Agency would all have to decide how to interpret and enforce rules in their respective fields. This will create'proportionate and adaptable regulation', it reckons, and regulators will be encouraged to consider'lighter touch options' which could include guidance and voluntary measures – which could presumably be ignored. There's more detail in the published paper, and the government has also invited various types in the know about AI as well as the regulators themselves to give some feedback on what it is suggesting, which will be considered alongside the development of another paper called the AI White Paper, which will explore how to put the principles into practice.

Ten years ago, the authors posited that being a data scientist was the “sexiest job of the 21st century.” A decade later, does the claim stand up? The job has grown in popularity and is generally well-paid, and the field is projected to experience more growth than almost any other by 2029. But the job has changed, in both large and small ways. It’s become better institutionalized, the scope of the job has been redefined, the technology it relies on has made huge strides, and the importance of non-technical expertise, such as ethics and change management, has grown. How it operates in companies — and how executives need to think about managing data science efforts — has changed, too, as businesses now need to create and oversee diverse data science teams rather than searching for data scientist unicorns. Finally, companies need to think about what comes next, and how they can begin to think about democratizing data science.

Deepfakes are more than silly games and pranks. At least on five accounts, they almost had the power to change the political course of entire countries. What many think of when hearing the word "deepfake" are viral videos of Tom Cruise "goofing around" on Tik Tok. Yet, it's the most harmless example of what a recording posing as a famous person can do. As seen in the video of Barack Obama created by Jordan Peele and BuzzFeed with the help of the latest AI technology, deepfakes can be rather convincing in posing as famous figures.