Abstract
In this digital era, we encounter automated decisions made about or on behalf of us by the so called Algorithmic Decision-Making (ADM) systems. While ADM systems can provide promising business opportunities, their implementation poses numerous challenges. Algorithmic bias that can enter these systems may result in systematical discrimination and unfair decisions by favoring certain individuals over others. Several approaches have been proposed to correct erroneous decision-making in the form of algorithmic bias. However, proposed remedies have mostly dealt with identifying algorithmic bias after the unfair decision has been made rather than preventing it. In this study, we use Delphi method to propose an ADM systems development process and identify sources of algorithmic bias at each step of this process together with remedies. Our outputs can pave the way to achieve ethics-by-design for fair and trustworthy ADM systems.
Original language | English |
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Title of host publication | Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020 |
Place of Publication | Honolulu |
Publisher | HICSS |
Pages | 5267-5276 |
Number of pages | 10 |
ISBN (Electronic) | 9780998133133 |
DOIs | |
Publication status | Published - 7 Jan 2020 |
Event | The 53rd Hawaii International Conference on System Sciences - Grand Wailea, Maui, United States Duration: 7 Jan 2020 → 10 Jan 2020 Conference number: 53 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=88330©ownerid=105104 |
Conference
Conference | The 53rd Hawaii International Conference on System Sciences |
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Abbreviated title | HICSS 2020 |
Country/Territory | United States |
City | Maui |
Period | 7/01/20 → 10/01/20 |
Internet address |
Keywords
- Delphi method
- algorithmic bias
- artificial inteligence
- ethics
- TRUSTWORTHY_AI