The growing ubiquity of algorithms in society: implications, impacts and innovations

By Sofia Charlotta Olhede, Patrick J. Wolfe. 2018

82 citations recorded by the source corpus.

The growing ubiquity of algorithms in society raises a number of fundamental questions concerning governance of data, transparency of algorithms, legal and ethical frameworks for automated algorithmic decision-making and the societal impacts of algorithmic automation itself. This article, an introduction to the discussion meeting issue of the same title, gives an overview of current challenges and opportunities in these areas, through which accelerated technological progress leads to rapid and often unforeseen practical consequences. These consequences—ranging from the potential benefits to human health to unexpected impacts on civil society—are summarized here, and discussed in depth by other contributors to the discussion meeting issue. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations'.

Subfields: Health Informatics, Information Systems, Safety Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Health Informatics

1. Paul Rodway
2. Astrid Schepman
3. Brent Daniel Mittelstadt
4. Emilio Ferrara

In Information Systems

1. Sandra Wachter
2. Paul Rodway
3. Astrid Schepman
4. Brent Daniel Mittelstadt

In Safety Research

1. Paul Rodway
2. Astrid Schepman
3. Brent Daniel Mittelstadt
4. Sandra Wachter
5. Chris Russell
6. Iason Gabriel
7. Emilio Ferrara
8. Eva Thelisson

Citations in the corpus

• Explaining Explanations in AI (2018, background): “…are not unique to computerised decision-making systems, but with the growth of machine learning based systems they have become even more important (Bodo et al., 2017; Kroll et al., 2016; Nissenbaum, 1996; Olhede and Wolfe, 2018; Pasquale, 2015; Selbst and Barocas, 2018; Veale and Edwards, 2018).”
• Bias in word embeddings (2020, background): “The growing ubiquity of algorithms in society poses questions about their social, political, and ethical consequences [77].”
• The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust (2022, background): “Society will be profoundly impacted by Artificial Intelligence (AI) over the next few decades (e.g., Makridakis, 2017; Olhede & Wolfe, 2018; Vesnic-Alujevic et al., 2020).”
• Initial validation of the general attitudes towards Artificial Intelligence Scale (2020, unknown): “We focused on workers, because they were likely to be affected by AI in both their personal sphere and their employment setting (Frontier Economics, 2018; Makridakis, 2017; Olhede & Wolfe, 2018), and therefore formed a useful dual-purpose sample.”