Artificial Intelligence & Financial Services

whitePaper | November 1, 2019

Artificial Intelligence is becoming an ever more important part of our lives. Many of us are already familiar with its everyday applications, such as decluttering our inboxes with spam filters or receiving personalised shopping recommendations. Yet, whether it is powering a new generation of self-driving cars, guarding us against fraud or helping doctors better diagnose health conditions, AI’s transformational abilities are being felt in increasingly ubiquitous and innovative ways.

whitePaper | March 30, 2022

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) offers the following submission for consideration in response to the Request for Information(RFI) by the White House Office of Science and Technology to the Update of the National Artificial Intelligence Research and Development Strategic Plan.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.

whitePaper | September 19, 2022

The field of artificial intelligence (AI) traces back to the 1950s. More recently, the increased availability of both data and computing power has bolstered rapid adoption of AI and machine learning (ML) solutions (collectively, AI/ML)

whitePaper | September 12, 2022

Artificial intelligence is currently attracting considerable interest and attention from industry, researchers, governments as well as investors, who are pouring record amounts of money into the development of new machine learning technologies and applications.

whitePaper | November 24, 2022

High-profile examples of harm associated with algorithm failure and misuse have garnered significant public concern (e.g. manipulation of the democratic process, discriminatory practice in criminal justice sentencing, and bias against racial and gender categories in the labour market). The field of AI ethics refers to the literature and to the community of people interested in this space. One high-profile manifestation of this is the formation of specialist ethics councils and teams to deliberate on conundrums regarding the use, access and openness of platforms and technologies (such as social media and messaging apps, etc.). For instance, the banning of particular public figures as well as lay users for use of the services in a manner that is not acceptable has been a constant theme in the public debate.