Towards Trustworthy Artificial Intelligent Systems

Preface
Acknowledgments
Contents
Artificial Intelligence: A Concept Under-Construction, A Reality Under-Development
1 A Concept Under-Construction
2 Natural Cognition: What Does [Intelligence] Stand for?
2.1 Basic Assumptions
2.2 The Three Common Key Existential Factors
2.3 The Specificity of Human Cognition
2.4 Representing Life Dynamics: The Need for a Non-mechanistic Approach
3 The Task of Replicating Intelligence
3.1 First Steps and the Way Forward
3.2 The Natural, the Artificial and Their Hybrid Forms
3.3 When Algorithms Couple with Data: The Digital Umwelt
4 Conclusion
References
In Machines We Trust?
1 Introduction
2 The Biological Roots of Trust
3 Trusting: The Glue of Interpersonal Relationships
4 The Concept of [Trust]: Defining Semantic Boundaries and Scope of Reference
5 Trusting Products
5.1 General Framework
5.2 The Case of Artificial Intelligent Systems
5.3 The Role of Benchmarking, Standardisation and Certification
5.4 Certification
6 Conclusions
References
Informational Privacy and Trust in Autonomous Intelligent Systems
1 Introduction
2 GDPR and Its Aims
3 GDPR & AIS—Case Examples
3.1 Ex-Ante Obligations: TOMs and DPIAs
3.2 Automated Decision Making
3.3 Transatlantic Transfers of Personal Data
4 Conclusions
Reference
Ethical Risk Assessment for Social Robots: Case Studies in Smart Robot Toys
1 Introduction
2 Ethical Risk Assessment
3 Case Study with a Fictional Smart Toy: RoboTed
3.1 Physical Risks
3.2 Psychological Risks
3.3 Privacy and Security Risks
3.4 Environmental Risks
3.5 Discussion of ERA for RoboTed
4 Case Study with Existing Smart Toy: Purrble
4.1 Physical Risks
4.2 Psychological Risks
4.3 Privacy and Security Risks
4.4 Environmental Risks
4.5 Discussion of ERA for Purrble
5 Discussion and Conclusions
References
Practical and Open Source Best Practices for Ethical Machine Learning
1 Introduction
2 Ethical Machine Learning
3 Best Practices in Machine Learning
3.1 Definition and Scope
3.2 Technical and Organisational BP
4 Conclusion
References
Recruitment AI Has a Disability Problem: Anticipating and Mitigating Unfair Automated Hiring Decisions
1 Introduction
2 Disability Marginalisation and Employment
3 Recruitment AI
4 Exclusion by Design and Discriminatory Use
4.1 Biased Systems
4.2 Improper Implementation and Use
5 AI on the Market: The Risks of Discrimination
5.1 ATS and CRM Systems
5.2 CV/Resume Screeners
5.3 Conversational Agents
5.4 Pre-employment Assessments
5.5 AI Interviewing
6 Intervention Recommendations
6.1 Executive Level Stakeholders
6.2 Human Resources Stakeholders
6.3 Procurement Stakeholders
6.4 Information Technology Stakeholders
References
Developing and Evaluating Complex Interventions: The Case of Robotic Systems in Cognitive Rehabilitation Therapy
1 Introduction
2 Complex Interventions: Definition and Scope
3 Robotics in Cognitive Rehabilitation Therapy (CRT)
4 Conclusions
References
COVID-19 Contact Tracing Applications in Portugal: Effectiveness and Privacy Issues
1 Introduction
2 COVID-19 Smartphone-Based Contact Tracing in Portugal
3 Contact Tracing Technologies
4 Analysis and Conclusions
References
Robots That Look After Grandma? A Gerontechnology Point of View
1 Robots That Look After Grandma
2 Gerontechnology, the Intersection Between Technology and Aging
3 Robots Used in Caring for Older Adults in Everyday Lives At Home
4 Building Ambient Intelligence to Support Older Adults and Caregivers
References
Making Maximally Ethical Decisions via Cognitive Likelihood and Formal Planning
1 Introduction
2 Cognitive Calculi
2.1 Deontic Cognitive Event Calculus
2.2 Inductive Deontic Cognitive Event Calculus
2.3 Cognitive Likelihood
3 Highly-Expressive Automated Planning
4 Selecting Plans Using Cognitive Likelihood
5 Case Study: The Miracle on the Hudson
5.1 Recounting US Airways Flight 1549
5.2 The Setup
5.3 The Arguments
5.4 The Framework, Applied
6 Related Work
7 Conclusion
References
The (Uncomputable!) Meaning of Ethically Charged Natural Language, for Robots, and Us, from Hypergraphical Inferential Semantics
1 Introduction
2 A Household-Robot Case Study
3 Prior Framework for Engineering of Robots Rodney and Ralph
4 Montagovian/Model-Theoretic Approach to Meaning, Rejected
4.1 MTS in Summary
4.2 Two Fatal Defects in Model-Theoretic Semantics
5 Proof-Theoretic Semantics (PTS)
5.1 The Basic Idea
5.2 But What About PTS for Natural Language?
6 Hypergraphical Inferential Semantics (mathscrH mathscrI mathscrS)
6.1 Intuitive Kernel of mathscrH mathscrI mathscrS via Buffalo-Buffalo-ellipsis…
6.2 Hypergraphical Natural Deduction
6.3 An Example: The Meaning of `Emma Helped'
7 Applying mathscrH mathscrI mathscrS to the Robot Case Study
8 Questions/Objections and Replies
8.1 Objection 1: Redundancies & Irrelevancies
8.2 Objection 2: Termination
8.3 Objection 3: How are Divine-command Theories and Codes Formalized?
8.4 Objection 4: OS-Level Ethical Controls Mysterious
9 Natural Language Understanding Is Provably Uncomputable
9.1 What of Prior and Related Work?
9.2 Descriptive Complexity
9.3 Computational Cognitive NLU
9.4 Computational Learning Theory
10 Future Work; Further Objections
References
Reinventing Kantian Autonomy for Artificial Agents: Implications for Self-driving Cars
1 Introduction
1.1 Robot Ethics as Applied Ethics
1.2 Agency
1.3 Moral Agency
1.4 Can Animals Be Moral Agents?
1.5 Autonomous Robots
2 Self-driving Vehicles
3 Conclusions
References
Realizing the Potential of AI in Africa: It All Turns on Trust
1 Introduction
2 The Benefits of AI Depend on Adoption and Trust
3 AI in Africa
4 Accelerating the Exploitation and Adoption of AI in Africa
5 The Downsides of AI
6 AI Education in Africa Is the Key to Progress
7 Conclusions
References
Index