In an age of ChatGPT, computer algorithms and artificial intelligence are increasingly embedded in our lives, choosing the content we're shown online, suggesting the music we hear and answering our questions. These algorithms may be changing our world and behavior in ways we don't fully understand, says psychologist and behavioral scientist Gerd Gigerenzer, the director of the Harding Center for Risk Literacy at the University of Potsdam in Germany. Previously director of the Center for Adaptive Behavior and Cognition at the Max Planck Institute for Human Development, he has conducted research over decades that has helped shape understanding of how people make choices when faced with uncertainty.

Given the growing use of artificial intelligence (AI) and automated decision-making tools in consumer-facing decisions, we expect federal regulators in 2022 to continue their recent track record of interest in potential discrimination and unfairness, as well as data accuracy and transparency. Significant technological developments in these areas and the increasing use of data analytics to make automated decisions will likely result in further regulatory action this year in three key areas: (1) assessing whether AI and algorithms are excluding particular consumer groups in an unfair and discriminatory manner, whether intentionally or not; (2) evaluating whether collected data accurately reflects real-world facts and whether companies are giving consumers an opportunity to correct mistakes; and (3) assessing whether automated decisionmaking tools are being used in a transparent manner. Over the last year, federal regulators with enforcement authority in the consumer space--the Federal Trade Commission (FTC) and the Consumer Financial Protection Bureau (CFPB)--have expressed their intention to continue enforcement efforts. The FTC has identified "technology companies and digital platforms," "bias in algorithms and biometrics," and "deceptive and manipulative conduct on the Internet" as among its top enforcement priorities for the coming years, and directed staff to use compulsory processes to demand documents and testimony to investigate potential abuses in these areas. The FTC and the CFPB have each initiated or continued investigations into practices involving the collection of consumer data and the use of data analytics in consumer decisions, including the use of AI and algorithms by financial institutions, digital payment platforms, and social media, and video streaming firms.

Monitoring of workers and setting performance targets through algorithms is damaging employees' mental health and needs to be controlled by new legislation, according to a group of MPs and peers. An "accountability for algorithms act'" would ensure that companies evaluate the effect of performance-driven regimes such as queue monitoring in supermarkets or deliveries-per-hour guidelines for delivery drivers, said the all-party parliamentary group (APPG) on the future of work. "Pervasive monitoring and target-setting technologies, in particular, are associated with pronounced negative impacts on mental and physical wellbeing as workers experience the extreme pressure of constant, real-time micro-management and automated assessment," said the APPG members in their report, the New Frontier: Artificial Intelligence at Work. The report recommends bringing in a new algorithms act, which it says would establish "a clear direction to ensure AI puts people first". It warns that "use of algorithmic surveillance, management and monitoring technologies that undertake new advisory functions, as well as traditional ones, has significantly increased during the pandemic".

The A-level results drama last month has placed a lot of attention on how algorithms are used in decision-making. As the use of AI expands, Esther Langdon looks at how organisations can make sure they get the best out of AI while keeping its outcomes fair. Artificial intelligence and algorithms have been very much in the news recently, following the recent A-level results fiasco. Can an algorithm eradicate bias in decision making? Stories of young students whose hopes were dashed simply because the "computer says no" made headlines for several days.

Here's an educated guess: Among all of the possible things employees are likely to miss from their jobs since they have been asked to stop coming in to the office, their boss is probably not one of them. Because there is an odd tendency across organizations to promote people into leadership roles regardless of their talent, and without giving them much prior training on how to be a good boss. The flawed assumption here is that as soon as employees perform well in their role, or are at least able to persuade others that they have, they should be asked to do something else. Ironically, their reward for being a valuable asset to the organization is to be put in charge of others, have them manage a team, and in effect stop them from doing what they are good at: their job. The common result is that they then become a less valuable asset to the organization.

Since their entrance into mainstream political consciousness, Artificial Intelligence (AI) and Big Data have long been a harbinger of political doom and a coming onslaught of global, geopolitical shifts. Movies, TV series, think pieces and tech reports paint and increasingly grim picture of power being handed over by governments and citizens to amorphous algorithms that govern with no transparency. The most dramatic depiction is the all-out data-driven apocalypse of the Terminator universe, but subtler, more intimate insights into our Data Hell come from Black Mirror, whose episodes shed light on people, relationships and societies that have sacrificed their subjectivity in the name of optimization. In the political sphere, a mainstream position in the Democratic party of the U.S. is that Russia stole the 2016 Presidential Election with advanced hacking tools and trolls. The emerging race between the U.S. and China to develop the most advanced AI is being called the Cold War of the 21st century; the central power struggle that defines an era for the world.

As is tradition, yesterday I attended IP EXPO at the London ExCel. Normally at these sort of events I don't have the time to make it to any of the various seminars taking place, but this time I made a conscious effort to make some time and I am pleased that I did. I managed to partake in a very interesting talk from Dr Hannah Fry titled: How to be human in the age of the machine. As I bumbled into an already packed out Keynote Theatre, flat white and notepad in hand, I wasn't really sure what to expect. Tech isn't the sexiest thing in the world, but Dr Fry made the whole talk incredibly engaging with jokes, anecdotes, visuals and a healthy dose of audience participation.

The holiday season has many things associated with it that generates positive emotions in people around the world. Sadly, it is also a time that generates negative feelings which includes suicidal thoughts. Although humans are getting better in understanding the human psyche, suicide among young adults is the second-leading cause of death according to the U.S. Centers for Disease Control and Prevention. Fortunately, artificial intelligence is improving in this field as algorithms are getting better at identifying human behavior. Let's first explain what an algorithm is, which is a procedure used to help find the answer to a mathematical problem (finding the greatest common divisor) in a number of finite steps which frequently involves repetition of an operation; in other words, a step-by-step procedure for figuring out the answer to a problem or accomplishing some end by using a computer.

The lights dimmed and a hush fell over the crowd. The last hour had been building to this. Denis Sverdlov, CEO of Roborace, and Daniel Simon, chief design officer, took a step back as some knee-high panels were taken away and a silky cloth was lifted, revealing a mechanical monster underneath. More than a year after the project's announcement, the pair had finally revealed their first production-grade Robocar: a fully electric, driverless race car built from the ground up for a new breed of motorsport. One where the heroes are programmers, concocting the smartest and most competitive AI drivers. The Robocar is an imposing sight.

Demand for non-equity trading algorithms serving institutional asset managers and retail investors is expanding the prevalence of artificial intelligence in the world's financial markets. A recent report by Thomson Reuters estimates that algorithmic trading systems now handle 75 per cent of the volume of global trades worldwide and this figure is predicted, by those in the industry, to grow steadily. Firstly, while the institutional market has enjoyed a large variety of "algos" serving the equity markets to date, other areas such as futures are still witnessing huge product demand and innovation as a result. Secondly, regulations affecting the institutional investment market, such as the European Union Markets in Financial Instruments Directive II or MiFID II, are pushing for greater automation of trades in some asset classes which traditionally were not executed electronically. The fixed income market is a prime example and negotiations between industry groups are ongoing as to how practical a fully automated fixed income could really be, given the magnitude of the required shift from telephone to electronic trading.