A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Building and Rebuilding Trust in
Algorithmic Systems
Gideon Ogunniye
Research Associate (ReEnTrust Project), AIAI, School of
Informatics, University of Edinburgh
January 18, 2021
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 1 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Overview
1 A little bit about Algorithms and Trust
The Impact of Algorithmic Systems
Algorithm bias
ReEnTrust Project
2 Sandbox Studies
Hotel Booking Scenario
E-recruitment Scenario
3 Trust Mediation Tool (suggestions welcomed)
Requirements
Inconsistencies and Preference Aggregation
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Impact
The public encounter algorithms indirectly through applications such
as:
predictive policing, sentencing and parole
medical decisions and diagnosis
credit scoring and financial decisions
And, directly through e-commerce services such as:
automated customer service assistants
hotel and holiday bookings
recommender systems
job recruitment
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Impact
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Context
Algorithms operate in a complicated socio-technical context that
includes :
the designers of the algorithms
the data used as an input to the algorithms
the interface that presents and uses the outputs
the people who make choices about goals of algorithms and
when to use algorithms
and societal laws and norms that influence their use
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 5 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Algorithm bias
Algorithmic-bias is the systematic and repeatable errors in the computational
outcomes that create a lack of fairness in the process.
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Algorithms in the news
Source:
https://www2.slideshare.net/AnsgarKoene/explorers-fair-talk-whoisincontrolyouthealgorithm
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Algorithms in the news
Source: https://towardsdatascience.com/algorithm-bias-in-artificial-intelligence-needs-to-be-discussed-and-addressed-8d369d675a70
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
The transparency challenge
Company algorithms provide a competitive edge which they are
reluctant to expose with non-disclosure agreements in place.
They also want to limit the ability of users to game the algorithm to
unfairly gain competitive advantage
Many algorithms are designed to be reactive and mutable to inputs.
E.g.: Facebook’s Newsfeed algorithm. Post are ordered dependent on
how one interacts with ‘friends’. The parameters are contextually
weighted and fluid.
In order cases, randomness might be buily into an algorithm’s design,
meaning its outcomes can never be perfectly predicted.
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 9 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
ReEnTrust Project
ReEnTrust explores new technological opportunities for platforms to
regain user trust and aims to identify how this may be achieved in
ways that are user-driven and responsible.
Focusing on AI algorithms and large-scale platforms used by the
general public, some of our research questions include:
What are user expectations and requirements regarding the rebuilding
of trust in algorithmic systems once that trust has been lost?
To what extent can user trust be regained through technological
solutions? What further trust rebuilding mechanisms might be
necessary and appropriate, including policy, regulation, and education?
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 10 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Sandbox studies
We investigate how users develop their trust perceptions of
algorithms;
by providing them with algorithm explanations;
and, an ability to explore different algorithmic behaviours by
filtering and querying algorithms
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 11 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Hotel booking scenario
To measure study participants’ self-reported perceptions:
Intelligibility: How well users can understand the mechanism by
which an algorithm works.
Correctness: How well users can think that an algorithm is
working as it is intended, and it’s not producing a mistake.
Fairness: How much users feel that an algorithm is unbiased
and has not treated any users unfairly in comparison to others.
Trustworthiness: How much users feel confident that the
algorithm has good intentions, is truthful, and is reliable.
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 12 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Hotel booking scenario
Explanations and Users’ Perceptions of Recommender Algorithms
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Hotel Booking Experimental Platform
Algorithm Playground
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Choice of Explanations
The how and why explanations provided in the study
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Participants’ Information (hotel booking scenario)
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Findings (hotel booking scenario)
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E-recruitment scenario
Understanding User Perceptions of Fairness, Reliability, Transparency
and Trustworthiness in E-recruitment Systems
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 18 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
E-Recruitment Experimental Platform
Algorithm Playground
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Participants’ information (e-recruitment scenario)
110 participants
48.2% male, 51.8% female
62.7% between the age of 26-35 years old
55.5% undergraduate degree highest completed education,
24.5% college graduate
96.4% UK resident (0.9% US and 0.9% Czech)
89.1% Employed full time
15.5% have previously worked in a position that involved hiring
candidates or working in recruitment
9.1% currently work in a position that involved hiring candidates
or working in recruitment
Of that 24.6%, 10.9% have 6 months to a year of experience,
7.3% between one and two years
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Findings (e-recruitment scenario)
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Concerns
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Trust Mediated Tool
What’s our overall aim?
The tool will provide the primary vehicle for validating what technical
solutions are possible when attempting to tackle the overall problem
of rebuilding trust between users and algorithms on online platforms.
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 23 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Trust Mediation Tool
Requirements:
Transparency
Openness of algorithms
Algorithm behaviours (accuracy, novelty, serendipity, etc)
useable and assessable
Fairness
Gender equality
Diversity-in-design
Political concerns?
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 24 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Trust Mediation Tool
Requirements (contd.):
Privacy vs personalisation
Trade-offs between data collection and control over personal
data
Accuracy vs personalisation
Trade-offs between accuracy and control over personal data
Fairness vs accuracy
Reducing disparities between groups without sacrificing the
overall performance of the model
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A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Trust Mediation Tool
Requirements (contd.):
Personal views
Collecting individual user’s concerns and preferences
Consensus views and mediated solutions
Aggregate users’ concerns
Preference aggregation
Recommendations based on aggregated views
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 26 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
PAF based on SIVs
In group decision making, there is always a problem of aggregating
the views of the individual agents of that group into a single collective
view that is desirable to the agents involved.
We have developed a new theoretical framework for restoring
consistency to knowledge bases and for resolving conflicting
preferences between multiple knowledge bases.
This Preference Aggregation Framework (PAFs) is based on
Shapley Inconsistency Values (SIVs).
The idea is to use SIVs to evaluate how each formula and rule in
an agent’s knowledge base contributes to the overall conflicts in
the combined knowledge base of all agents.
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 27 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Expected Outcomes
Implemented prototypes of trust rebuilding tools.
Experimental results validating the benefits derived from use of
these tools.
Gideon Ogunniye AIAI Seminar: 18th January 2021 January 18, 2021 28 / 30

A little bit about Algorithms and Trust Sandbox Studies Trust Mediation Tool (suggestions welcomed)
Conclusions
Trust must be engendered in order to maximise the benefits that
algorithms provide.
We are interested in the following:
1 Quantification of algorithmic trust as a metric
2 How algorithmic technology is developing
3 New suggested approaches to regain public trust in algorithms
4 The potential role of algorithms and platforms in a post-COVID,
post-Brexit UK
5 Other public policy areas that are related to or can feed into our
piece of work
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Thank you
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