Brent Mittelstadt

University of Oxford | OX · Oxford Internet Institute

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, a...

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that a 'right to explanation' of decisions made by automated or artificially intelligent algorithmic systems will be legally mandated by the GDPR. This right to explanation is viewed as an ideal mechanism to enhance the accountabili...

This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first d...

There has been much discussion of the right to explanation in the EU General Data Protection Regulation, and its existence, merits, and disadvantages. Implementing a right to explanation that opens the black box of algorithmic decision-making faces major legal and technical barriers. Explaining the functionality of complex algorithmic decision-maki...

Columbia Business Law Review, 2019(2). Big Data analytics and artificial intelligence (AI) draw non-intuitive and unverifiable inferences and predictions about the behaviors, preferences, and private lives of individuals. These inferences draw on highly diverse and feature-rich data of unpredictable value, and create new opportunities for discrimi...

Fine-tuning language models has become increasingly popular following the proliferation of open models and improvements in cost-effective parameter efficient fine-tuning. However, fine-tuning can influence model properties such as safety. We assess how fine-tuning can impact different open models' propensity to output toxic content. We assess the i...

Careless speech is a new type of harm created by large language models (LLM) that poses cumulative, long-term risks to science, education and shared social truth in democratic societies. LLMs produce responses that are plausible, helpful and confident, but that contain factual inaccuracies, misleading references and biased information. These subtle...

We present OxonFair, a new open source toolkit for enforcing fairness in binary classification. Compared to existing toolkits: (i) We support NLP and Computer Vision classification as well as standard tabular problems. (ii) We support enforcing fairness on validation data, making us robust to a wide range of overfitting challenges. (iii) Our approa...

As generative Artificial Intelligence (genAI) technologies proliferate across sectors, they offer significant benefits but also risk exacerbating discrimination. This chapter explores how genAI intersects with non-discrimination laws, identifying shortcomings and suggesting improvements. It highlights two main types of discriminatory outputs: (i) d...

Access to resources strongly constrains the decisions we make. While we might wish to offer every student a scholarship, or schedule every patient for follow-up meetings with a specialist, limited resources mean that this is not possible. Existing tools for fair machine learning ignore these key constraints, with the majority of methods disregardin...

This article examines whether the EU Medical Device Regulation (MDR) adequately addresses the novel risks of AI-based medical devices (AIaMDs), focusing on AI medical imaging tools. It examines two questions: first, does the MDR effectively deal with issues of adaptability, autonomy, bias, opacity, and the need of trustworthiness of AIaMD? Second,...

In recent years, fairness in machine learning (ML), artificial intelligence (AI), and algorithmic decision-making systems has emerged as a highly active area of research and development. To date, most measures and methods to mitigate bias and improve fairness in algorithmic systems have been built in isolation from policymaking and civil societal c...

The technical progression of artificial intelligence (AI) research has been built on breakthroughs in fields such as computer science, statistics, and mathematics. However, in the past decade AI researchers have increasingly looked to the social sciences, turning to human interactions to solve the challenges of model development. Paying crowdsourci...

Artificial intelligence (AI) is increasingly relied upon by clinicians for making diagnostic and treatment decisions, playing an important role in imaging, diagnosis, risk analysis, lifestyle monitoring, and health information management. While research has identified biases in healthcare AI systems and proposed technical solutions to address these...

Firms are increasingly personalising their offers and services, leading to an ever finer-grained segmentation of consumers online. Targeted online advertising and online price discrimination are salient examples of this development. While personalisation's overall effects on consumer welfare are expectably ambiguous, it can lead to concentration in...

To achieve the promoted benefits of an AI symptom checker, laypeople must trust and subsequently follow its instructions. In AI, explanations are seen as a tool to communicate the rationale behind black-box decisions to encourage trust and adoption. However, the effectiveness of the types of explanations used in AI-driven symptom checkers has not y...

Background Artificial intelligence (AI)–driven symptom checkers are available to millions of users globally and are advocated as a tool to deliver health care more efficiently. To achieve the promoted benefits of a symptom checker, laypeople must trust and subsequently follow its instructions. In AI, explanations are seen as a tool to communicate t...

In its attempt to better regulate the platform economy, the European Commission recently proposed a Digital Markets Act (DMA) and a Digital Services Act (DSA). While the DMA addresses worries about digital markets not functioning properly, the DSA is concerned with societal harms stemming from the dissemination of (illegal) content on platforms. Bo...

In recent years a substantial literature has emerged concerning bias, discrimination, and fairness in artificial intelligence (AI) and machine learning. Connecting this work to existing legal non-discrimination frameworks is essential to create tools and methods that are practically useful across divergent legal regimes. While much work has been un...

Online targeting isolates individual consumers, causing what we call epistemic fragmentation. This phenomenon amplifies the harms of advertising and inflicts structural damage to the public forum. The two natural strategies to tackle the problem of regulating online targeted advertising, increasing consumer awareness and extending proactive monitor...

Online behavioural advertising (OBA) relies on inferential analytics to target consumers based on data about their online behaviour. While the technology can improve the matching of adverts with consumers’ preferences, it also poses risks to consumer welfare as consumers face offer discrimination and the exploitation of their cognitive errors. The...

BACKGROUND Artificial intelligence (AI)–driven symptom checkers are available to millions of users globally and are advocated as a tool to deliver health care more efficiently. To achieve the promoted benefits of a symptom checker, laypeople must trust and subsequently follow its instructions. In AI, explanations are seen as a tool to communicate t...

We invited authors of selected Comments and Perspectives published in Nature Machine Intelligence in the latter half of 2019 and first half of 2020 to describe how their topic has developed, what their thoughts are about the challenges of 2020, and what they look forward to in 2021.

Background: Dementia has been described as the greatest global health challenge in the 21st century on account of longevity gains increasing its incidence, escalating health and social care pressures. These pressures highlight ethical, social, and political challenges about healthcare resource allocation, what health improvements matter to patient...

Background Dementia has been described as the greatest global health challenge in the 21st century on account of longevity gains increasing its incidence, escalating health and social care pressures. These pressures highlight ethical, social, political challenges about healthcare resource allocation, what health improvements matter to patients, and...

Background: The therapeutic paradigm in Alzheimer's disease (AD) is shifting from symptoms management toward prevention goals. Secondary prevention requires the identification of individuals without clinical symptoms, yet "at-risk" of developing AD dementia in the future, and thus, the use of predictive modeling. Objective: The objective of this...

This article identifies a critical incompatibility between European notions of discrimination and existing statistical measures of fairness. First, we review the evidential requirements to bring a claim under EU non-discrimination law. Due to the disparate nature of algorithmic and human discrimination, the EU's current requirements are too context...

Artificial intelligence (AI) ethics is now a global topic of discussion in academic and policy circles. At least 84 public–private initiatives have produced statements describing high-level principles, values and other tenets to guide the ethical development, deployment and governance of AI. According to recent meta-analyses, AI ethics has seemingl...

AI Ethics is now a global topic of discussion in academic and policy circles. At least 63 public-private initiatives have produced statements describing high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. According to recent meta-analyses, AI Ethics has seemingly converged on a set of...

ROADMAP is a public-private advisory partnership to evaluate the usability of multiple data sources, including real-world evidence, in the decision-making process for new treatments in Alzheimer’s disease, and to advance key concepts in disease and pharmacoeconomic modeling. ROADMAP identified key disease and patient outcomes for stakeholders to m...

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system m...

Big Data analytics and artificial intelligence (AI) draw non-intuitive and unverifiable inferences and predictions about the behaviors, preferences, and private lives of individuals. These inferences draw on highly diverse and feature-rich data of unpredictable value, and create new opportunities for discriminatory, biased, and invasive decision-ma...

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence (AI). In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to...

Recent years have seen an influx of medical technologies capable of remotely monitoring the health and behaviours of individuals to detect, manage and prevent health problems. Known collectively as ‘Personal Health Monitoring’ (PHM), these systems are intended to supplement medical care with health monitoring outside traditional care environments s...

Mature information societies are characterised by mass production of data that provide insight into human behaviour. Analytics (as in big data analytics) has arisen as a practice to make sense of the data trails generated through interactions with networked devices, platforms and organisations. Persistent knowledge describing the behaviours and cha...

The internet of things is increasingly spreading into the domain of medical and social care. Internet-enabled devices for monitoring and managing the health and well-being of users outside of traditional medical institutions have rapidly become common tools to support healthcare. Health-related internet of things (H-IoT) technologies increasingly p...

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time...

Full text openly available via direct link at: http://digitalethicslab.oii.ox.ac.uk/sandra-wachter/#tab-7456a56b194183e7f18 To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.

Do we have a right to transparency when we use content personalization systems? Building on prior work in discrimination detection in data mining, I propose algorithm auditing as a compatible ethical duty for providers of content personalization systems to maintain the transparency of political discourse. I explore barriers to auditing that reveal...

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometime...

Computing technologies and artifacts are increasingly integrated into most aspects of our professional, social, and private lives. One consequence of this growing ubiquity of computing is that it can have significant ethical implications that computing professionals need to be aware of. The relationship between ethics and computing has long been di...

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use...

Empirical research into the ethics of emerging technologies, often involving foresight studies, technology assessment or application of the precautionary principle, raises significant epistemological challenges by failing to explain the relative epistemic status of contentious normative claims about future states. This weakness means that it is unc...

Internet engineering and networked systems research improves our understanding of the underlying technical processes of the Internet. Internet engineers therefore analyse data transfers on the Internet, typically by collecting data from devices of large groups of individuals as well as organisations. The designs of Internet engineering and research...

The capacity to collect and analyse data is growing exponentially. Referred to as 'Big Data', this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometime...

Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes...

Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes...

Value-Sensitive Design (VSD) offers a methodology to make social and moral values central to the design and development of new technologies. Although VSD incorporates views from philosophy and stakeholders involved in the process, it notably lacks reflexivity on the position of those involved in conducting the methodology itself e.g. ethicists, res...

Value-Sensitive Design (VSD) offers a methodology to make social and moral values central to the design and development of new technologies. Although VSD incorporates views from philosophy and stakeholders involved in the process, it notably lacks reflexivity on the position of those involved in conducting the methodology itself e.g. ethicists, res...

The chapter undertakes a comparison of different approaches to the ethical assessment of novel technologies by looking at two recent research projects. ETICA was a FP7 sister project to PHM-Ethics, responsible for identification and ethical evaluation of information and communication technologies emerging in the next 10-15 years. The aims, methods,...

Personal health monitoring (PHM) systems capable of gathering pervasive physiological and behavioural data are currently in development to supplement existing medical resources. As a technology designed to operate in the private sphere, PHM can digitise, record and analyse the lives of patients, creating opportunities for data sharing, mining and s...

Personal health monitoring (PHM) systems capable of gathering pervasive physiological and behavioural data are currently emerging to supplement existing medical resources. As a technology designed to operate in the private sphere PHM can digitise, record and analyse the behaviours and health of users. Current PHM ethics discourse reflects an overly...

A unified perspective on data protection is set to be adopted in the EU through the General Data Protection Legislation, which intended to unite and simplify disparate legislation currently enacted at a national level. Such legislation contributes to the definition of responsible research and innovation by defining norms of legal and ethically acce...

Personal Health Monitoring describes a broad group of emerging health ICT developed in response to changing demographics and health needs in the EU. Based upon a review of academic literature, this contribution to the FRRIICT repository defines PHM and identifies ethical implications requiring further consideration by the ICT community. Examples an...