Free online course created by the Governance Lab (The GovLab), NYU Tandon School of Engineering, Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and Technical University of Munich (TUM) Institute for Ethics in Artificial Intelligence (IEAI). Launched on February 1, 2021. A Collection of Lectures on the Ethical implications of Data and Artificial Intelligence from Different Perspectives.
From the Website:
Data-intensive and AI-based technologies can solve the world’s biggest challenges, but they also pose risks to individuals and groups. As we deploy new technology, we must consider ethical ramifications of AI use to identify and rectify harms.
Responsible design and use of AI is difficult, but there is an urgent need for it amid the crisis. When organizations adopt new technologies without regard to the wider social, economic, cultural, and political contexts, they can endanger privacy and security and exacerbate inequities in ways that are difficult to reverse.
This course is designed to raise awareness of the societal impacts of technology and to give individuals and institutions the tools to pursue responsible AI use. Intended for current and future data scientists, policymakers, and business leaders, this course contains 19 modules on topics related to artificial intelligence. Each module consists of a video lecture accompanied by additional resources such as podcasts, videos, and readings.
Join us as we seek to create a more nuanced understanding of the role that AI can—and should—play in society.
Ethical Surveillance: Regulating for personal and surveillance data in COVID-19 control conditions
This lecture reviews the ethical challenges—discrimination, lack of transparency, neglect of individual rights, and more—which have arisen from COVID-19 technologies and the resultant mass data accumulation. — Mark Findlay and Nydia Remolina
AI for whom?
This module asks and answers the question, “Who is artificial intelligence for?” It presents evidence that AI systems do not always help their intended users and constituencies. — Danya A Glabau
Alexa vs Alice: Cultural Perspectives on the Impact of AI
This course explores the importance of considering the cultural, geographical, and temporal aspects of AI to correctly develop and implement AI systems. — Idoia Salazar
Applications of Artificial Intelligence (AI) in Transport and Safety
This course sheds light on the fundamentals of Artificial Intelligence in Transportation System (AITS) and safety, and looks at the technologies at play in its implementation. — Jerry John Kponyo
Responsible Engineering Design and Innovation of AI Systems
Rafael Calvo describes a framework for the human impact assessment of technology, Motivation Engagement and Thriving in User Experience (METUX), which incorporates psychological needs in the design of AI Systems and other technologies. — Rafael Calvo
AI and the Future of Education
Kan Suzuki discusses the need to reform education systems to successfully confront the risks and opportunities associated with development of AI. — Kan Suzuki
Indigenous Data Sovereignty
This course unpacks the idea of indigenous data sovereignty, and associated principles, frameworks, challenges. Professor Hudson also discusses Maori approaches to Artificial Intelligence and what it means to indigenize AI. — Maui Hudson
The Intersection of AI and Consumer Protection
This lecture considers the use of consumer data in advertising for goods and services, the harms that this strategy may cause to consumer welfare and to market competition, and strategies in consumer protection law that might be used to respond to these possible harms. — Jeannie Paterson
The Responsible Use of AI in Organizations
This module proposes guidelines for organizations committed to the responsible use of AI, but lack required knowledge and experience. — Dr. Richard Benjamins
Content Moderation in Social Media and AI
We love to communicate. We love to share. We love to debate, exchange – sometimes vigorously. This is why we developed social media. But, the proliferation of social media has also raised several concerns. How do we fix this? — Serge Abiteboul
Algorithmic Bias and Relativity in AI
This module discusses one of the most pressing ethical concerns pertaining to AI: algorithmic bias. It also investigates the fundamental “relativity” of AI by focusing on various examples from two specific specialties – music and physics. — Ken Ito
Do Carebots Care? The Ethics of Social Robots in Care Settings
This module explores the ethical implications of robotics, and in particular, the ethical issues that emerge from social robots deployed in care settings (“Carebots”). — Shannon Vallor
Artificial Intelligence: Perspectives from the Global South
In this module, Celina and Fabro discuss various global agendas for AI development, and why AI systems should take into consideration both local and global perspectives. — Fabro Steibel and Celina Bottino
Building Data Equity Systems
This module presents a vision for data equity systems – systems that consider equity as an essential objective. It speaks to technologists, helping them understand the role of technical interventions in making the world more equitable and just. — Julia Stoyanovich (Course Lead)
Profiling in the Age of AI
Today, various technologies – IOT, big data, and artificial intelligence – are applied to radically alter methods and impacts of profiling. This lecture explores the need for a rethought and renewed regulatory framework for profiling in a digital environment. — Yves Poullet
AI Powered Disability Discrimination: How Do You Lip Read a Robot Recruiter?
This module explores the unacknowledged risks to the world’s more than 1.3 billion persons with disabilities triggered by the growing use of AI powered Human Resources Technology, asking: why is the AI industry ignoring human reality? — Susan Scott-Parker
Examining use cases of AI at a local level across housing, urban planning, public service, citizen engagement, energy, education, safety, and social care sectors, Stefaan sheds light on novel ways local governments are implementing and regulating AI. — Stefaan Verhulst (Course Lead)
Will the Market Deliver? A Business Ethics Perspective to AI
This module develops a business ethics perspective on AI. After exploring the concept of AI, its ethical relevance and specific properties, the presentation addresses areas where companies can utilize AI in order to address business ethics specific issues. — Christoph Lütge (Course Lead)