IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v7y2020i1d10.1057_s41599-020-0501-9.html
   My bibliography  Save this article

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Author

Listed:
  • Samuele Lo Piano

    (University of Reading
    Universitat Oberta de Catalunya)

Abstract

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning (ML) algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. ML approaches—one of the typologies of algorithms underpinning artificial intelligence—are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision-making are outlined: (a) risk assessment in the criminal justice system, and (b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined.

Suggested Citation

  • Samuele Lo Piano, 2020. "Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-7, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-0501-9
    DOI: 10.1057/s41599-020-0501-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-020-0501-9
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-020-0501-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jeroen P. Van Der Sluijs & Matthieu Craye & Silvio Funtowicz & Penny Kloprogge & Jerry Ravetz & James Risbey, 2005. "Combining Quantitative and Qualitative Measures of Uncertainty in Model‐Based Environmental Assessment: The NUSAP System," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 481-492, April.
    2. Andrea Saltelli, 2019. "A short comment on statistical versus mathematical modelling," Nature Communications, Nature, vol. 10(1), pages 1-3, December.
    3. Bilal HMOUD & Varallyai LASZLO, 2019. "Will Artificial Intelligence Take Over Humanresources Recruitment And Selection?," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 13, pages 21-30, July.
    4. Siddharth Sareen & Andrea Saltelli & Kjetil Rommetveit, 2020. "Ethics of quantification: illumination, obfuscation and performative legitimation," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-5, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xia Liu & Yanhan Sun & Shengshi Zhou & Yu Li & Shan Zhuang, 2024. "Research on time-value-oriented business model innovation path in life services enterprises and its impact on customer perceived value," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    2. Stephen C. Slota & Kenneth R. Fleischmann & Sherri Greenberg & Nitin Verma & Brenna Cummings & Lan Li & Chris Shenefiel, 2023. "Locating the work of artificial intelligence ethics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(3), pages 311-322, March.
    3. Koefer, Franziska & Lemken, Ivo & Pauls, Jan, 2023. "Fairness in algorithmic decision systems: A microfinance perspective," EIF Working Paper Series 2023/88, European Investment Fund (EIF).
    4. Federico Fioravanti & Iyad Rahwan & Fernando Tohmé, 2022. "Properties of Aggregation Operators Relevant for Ethical Decision Making in Artificial Intelligence," Working Papers 177, Red Nacional de Investigadores en Economía (RedNIE).
    5. Athanasios Polyportis & Nikolaos Pahos, 2024. "Navigating the perils of artificial intelligence: a focused review on ChatGPT and responsible research and innovation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    6. Annye Braca & Pierpaolo Dondio, 2023. "Developing persuasive systems for marketing: the interplay of persuasion techniques, customer traits and persuasive message design," Italian Journal of Marketing, Springer, vol. 2023(3), pages 369-412, September.
    7. Raza, Syed Arshad, 2021. "Managing ethical requirements elicitation of complex socio-technical systems with critical systems thinking: A case of course-timetabling project," Technology in Society, Elsevier, vol. 66(C).
    8. Meir Russ, 2021. "Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models," Sustainability, MDPI, vol. 13(6), pages 1-32, March.
    9. Ola Michalec & Cian O’Donovan & Mehdi Sobhani, 2021. "What is robotics made of? The interdisciplinary politics of robotics research," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    10. Andrea Saltelli & Monica Fiore, 2020. "From sociology of quantification to ethics of quantification," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    11. Lachlan O'Neill & Simon D Angus & Satya Borgohain & Nader Chmait & David Dowe, 2021. "Creating Powerful and Interpretable Models with Regression Networks," SoDa Laboratories Working Paper Series 2021-09, Monash University, SoDa Laboratories.
    12. Federico Fioravanti & Iyad Rahwan & Fernando Abel Tohm'e, 2022. "Classes of Aggregation Rules for Ethical Decision Making in Automated Systems," Papers 2206.05160, arXiv.org, revised Jun 2023.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrea Saltelli & Monica Fiore, 2020. "From sociology of quantification to ethics of quantification," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    2. Marta Kuc-Czarnecka & Samuele Lo Piano & Andrea Saltelli, 2020. "Quantitative Storytelling in the Making of a Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 775-802, June.
    3. Siddharth Sareen & Andrea Saltelli & Kjetil Rommetveit, 2020. "Ethics of quantification: illumination, obfuscation and performative legitimation," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-5, December.
    4. Clive L Spash, 2009. "Social Ecological Economics," Socio-Economics and the Environment in Discussion (SEED) Working Paper Series 2009-08, CSIRO Sustainable Ecosystems.
    5. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    6. Wen, Xin & Heinisch, Verena & Müller, Jonas & Sasse, Jan-Philipp & Trutnevyte, Evelina, 2023. "Comparison of statistical and optimization models for projecting future PV installations at a sub-national scale," Energy, Elsevier, vol. 285(C).
    7. Ides Boone & Yves Van der Stede & Jeroen Dewulf & Winy Messens & Marc Aerts & Georges Daube & Koen Mintiens, 2010. "NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment," Journal of Risk Research, Taylor & Francis Journals, vol. 13(3), pages 337-352, April.
    8. Failing, L. & Gregory, R. & Harstone, M., 2007. "Integrating science and local knowledge in environmental risk management: A decision-focused approach," Ecological Economics, Elsevier, vol. 64(1), pages 47-60, October.
    9. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    10. Nuno Ligeiro & Ivo Dias & Ana Moreira, 2024. "Recruitment and Selection Process Using Artificial Intelligence: How Do Candidates React?," Administrative Sciences, MDPI, vol. 14(7), pages 1-17, July.
    11. Samuele Lo Piano & Lorenzo Benini, 2022. "A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 763-781, June.
    12. Siddharth Sareen, 2020. "Social and technical differentiation in smart meter rollout: embedded scalar biases in automating Norwegian and Portuguese energy infrastructure," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    13. Jill Walker Rettberg, 2020. "Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    14. Zhisheng Chen, 2023. "Ethics and discrimination in artificial intelligence-enabled recruitment practices," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    15. Magdalena Graczyk-Kucharska & Robert Olszewski & Gerhard-Wilhelm Weber, 2023. "The use of spatial data mining methods for modeling HR challenges of generation Z in greater Poland Region," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 205-237, March.
    16. Kaatje Bollaerts & Winy Messens & Marc Aerts & Jeroen Dewulf & Dominiek Maes & Koen Grijspeerdt & Yves Van der Stede, 2010. "Evaluation of Scenarios for Reducing Human Salmonellosis Through Household Consumption of Fresh Minced Pork Meat," Risk Analysis, John Wiley & Sons, vol. 30(5), pages 853-865, May.
    17. Marta Kuc-Czarnecka & Magdalena Olczyk, 2020. "How ethics combine with big data: a bibliometric analysis," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
    18. Sibel Eker, 2020. "Validity and usefulness of COVID-19 models," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-5, December.
    19. Muhamad Khalil Omar & Idaya Husna Mohd & Mohd Zulhafiz Wan Zahari & Nurhidayah Azmy, 2024. "Hybrid Skills Framework in The IR4.0 and Recruitment Decisions in Hiring Graduates: A Malaysian Employer’s Perspective," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(7), pages 252-273, July.
    20. Langdalen, Henrik & Abrahamsen, Eirik Bjorheim & Abrahamsen, HÃ¥kon Bjorheim, 2020. "A New Framework To Idenitfy And Assess Hidden Assumptions In The Background Knowledge Of A Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 200(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-0501-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.