Related papers: Transparency, Governance and Regulation of Algorit…
The notion that algorithmic systems should be "transparent" and "explainable" is common in the many statements of consensus principles developed by governments, companies, and advocacy organizations. But what exactly do policy and legal…
In today's world of computers, any kind of information can be made available within few clicks for different endeavors. The information may be tampered by changing the statistical properties and can be further used for criminal activities.…
This two part paper argues that seemingly "technical" choices made by developers of machine-learning based algorithmic tools used to inform decisions by criminal justice authorities can create serious constitutional dangers, enhancing the…
This two-part paper argues that seemingly "technical" choices made by developers of machine-learning based algorithmic tools used to inform decisions by criminal justice authorities can create serious constitutional dangers, enhancing the…
Machine learning systems are increasingly used to support public sector decision-making across a variety of sectors. Given concerns around accountability in these domains, and amidst accusations of intentional or unintentional bias, there…
Exploring the socio-technical challenges confronting the adoption of AI in organisational settings is something that has so far been largely absent from the related literature. In particular, research into requirements for trustworthy AI…
This article surveys the use of algorithmic systems to support decision-making in the public sector. Governments adopt, procure, and use algorithmic systems to support their functions within several contexts -- including criminal justice,…
There has been a surge in the number and type of AI tools being tested and deployed within both national and local government in the UK, including within the social care sector. Given the many ongoing and planned future developments, the…
Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace. How might designers support such human values? We…
Although deceptive design patterns are subject to growing regulatory oversight, enforcement races to keep up with the scale of the problem. One promising solution is automated detection tools, many of which are developed within academia. We…
Big data and algorithmic risk prediction tools promise to improve criminal justice systems by reducing human biases and inconsistencies in decision making. Yet different, equally-justifiable choices when developing, testing, and deploying…
Commercial or in-house developments of probabilistic AI systems are introduced in policing and the wider criminal justice (CJ) system worldwide, often on a force-by-force basis. We developed a systematic way to characterise probabilistic AI…
Evaluating the safety of AI Systems is a pressing concern for organizations deploying them. In addition to the societal damage done by the lack of fairness of those systems, deployers are concerned about the legal repercussions and the…
Transparency is often deemed critical to enable effective real-world deployment of intelligent systems. Yet the motivations for and benefits of different types of transparency can vary significantly depending on context, and objective…
Algorithmic systems make decisions that have a great impact in our lives. As our dependency on them is growing so does the need for transparency and holding them accountable. This paper presents a model for evaluating how transparent these…
The ability to get and keep a job is a key aspect of participating in society and sustaining livelihoods. Yet the way decisions are made on who is eligible for jobs, and why, are rapidly changing with the advent and growth in uptake of…
Artificial intelligence (AI) is increasingly being adopted in most industries, and for applications such as note taking and checking grammar, there is typically not a cause for concern. However, when constitutional rights are involved, as…
In recent years, discussions about fairness in machine learning, AI ethics and algorithm audits have increased. Many entities have developed framework guidance to establish a baseline rubric for fairness and accountability. However, in…
Combining big data and machine learning algorithms, the power of automatic decision tools induces as much hope as fear. Many recently enacted European legislation (GDPR) and French laws attempt to regulate the use of these tools. Leaving…
The integration of artificial intelligence (AI) and optimization hold substantial promise for improving the efficiency, reliability, and resilience of engineered systems. Due to the networked nature of many engineered systems, ethically…