| EPSRC Reference: |
EP/R033846/1 |
| Title: |
Realising Accountable Intelligent Systems (RAInS) |
| Principal Investigator: |
Edwards, Professor P |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computing Science |
| Organisation: |
University of Aberdeen |
| Scheme: |
Standard Research |
| Starts: |
01 January 2019 |
Ends: |
31 December 2021 |
Value (£): |
789,003
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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06 Mar 2018
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DE TIPS 2
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Announced
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Summary on Grant Application Form |
Intelligent systems technologies are being utilised in more and more scenarios including autonomous vehicles, smart home appliances, public services, retail and manufacturing. But what happens when such systems fail, as in the case of recent high-profile accidents involving autonomous vehicles? How are such systems (and their developers) held to account if they are found to be making biased or unfair decisions? Can we interrogate intelligent systems, to ensure they are fit for purpose before they're deployed? These are all real and timely challenges, given that intelligent systems will increasingly affect many aspects of everyday life.
While all new technologies have the capacity to do harm, with intelligent systems it may be difficult or even impossible to know what went wrong or who should be held responsible. There is a very real concern that the complexity of many AI technologies, the data and interactions between the surrounding systems and workflows, will reduce the justification for consequential decisions to "the algorithm made me do it", or indeed "we don't know what happened". And yet the potential for such systems to outperform humans in accuracy of decision-making, and even safety suggests that the desire to use them will be difficult to resist. The question then is how we might endeavour to have the best of both worlds. How can we benefit from the superhuman capacity and efficiency that such systems offer without giving up our desire for accountability, transparency and responsibility? How can we avoid a stalemate choice between forgoing the benefits of automated systems altogether or accepting a degree of arbitrariness that would be unthinkable in society's usual human relationships?
Working closely with a range of stakeholders, including members of the public, the legal profession and technology companies, we will explore what it means to realise future intelligent systems that are transparent and accountable. The Accountability Fabric is our vision of a future computational infrastructure supporting audit of such systems - somewhat analogous to (but more sophisticated than) the 'blackbox' flight recorders associated with passenger aircraft. Our work will increase transparency not only after the fact, but also in a manner which allows for early interrogation and audit which in turn may help to prevent or to mitigate harm ex ante. Before we can realise the Accountability Fabric, several key issues need to be investigated:
What are the important factors that influence citizen's perceptions of trust and accountability of intelligent systems?
What form ought legal liability take for intelligent systems? How can the law operate fairly and incentivize optimal behaviour from those developing/using such systems?
How do we formulate an appropriate vocabulary with which to describe and characterise intelligent systems, their context, behaviours and biases?
What are the technical means for recording the behaviour of intelligent systems, from the data used, the algorithms deployed, and the flow-on effects of the decisions being made?
Can we realise an accountability solution for intelligent systems, operating across a range of technologies and organisational boundaries, that is able to support third party audit and assessment?
Answers to these (and the many other questions that will certainly emerge) will lead us to develop prototype solutions that will be evaluated with project partners. Our ambition is to create a means by which the developer of an intelligent system can provide a secure, tamper-proof record of the system's characteristics and behaviours that can be shared (under controlled circumstances) with relevant authorities in the event of an incident or complaint.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.abdn.ac.uk |