The ethics of algorithms: Mapping the debate

Abstract

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, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

A Constructionist Philosophy of Logic

“…Again, we can remark how, this time in a fully formalised context, explicit concepts and proof-procedures together with the conceptual and technological means to efficiently use and verify these concepts and procedures can be used to certify the epistemic reliability of mathematical results. Mittelstadt et al (2016) for a recent survey of the debate, and Hildebrandt (2016) for a discussion of the preconditions of contestation. 21 On the implications of the use of proof-assistants based on formal type-theory for the older debate on the four-colour theorem, see Arkoudas and Bringsjord (2007).…”

Gender bias in machine learning for sentiment analysis

“…This could lead to adverts for programmers to be delivered mainly to male users, targeting women with home appliance offers instead. Thus, algorithms can deliver misguided information, leading to bias in system outputs (such as adverts or search results) or the conclusions drawn by a human from these outputs (Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016).…”

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

“…For instance, being provided with thousands of printed pages of data would require unreasonable effort on the part of the data subject when more efficient formats are available, and would therefore fail to preserve a meaningful right to access. Comprehension also poses a challenge; "Big Data" requires significant computational power and storage, and advanced scientific know-how [31,32]. As with any type of data science, analysis requires discipline-specific skills and knowledge, often only accessible through extensive training and education.…”

“…Ideally, these disclosures will also include some explanation of the methods and algorithms used to make sense of H-IoT data [68], including profiling measures and the impact of profiling on choices available to the user. The difficulties of such explanations in lay language must be acknowledged; different levels of technical detail, vocabulary and communication media will be required [24,31,32]. User-centric design, as supported by the principle of inclusiveness, can help assess the capacities and needs of different user groups.…”