Data Ethics, AI and Responsible Innovation
How much would you like your smart home to know about you? Has your data been harvested and used for political advertising on social media? Would you be happy to be profiled by a predictive policing AI?
As we create more data-driven technologies, those issues become increasingly urgent. We must begin to ask not only ‘what can we do?’, but also ‘what should we do?’ How should we design new technologies to make sure they are used for good, not bad purposes?
The ‘good’, the ‘bad’, and the ‘should’ are a domain of ethics, and a basis for other important concepts such as justice, fairness, rights, respect. They further inform the law and what is legal. Finally, they are at the roots of an extremely important currency in the modern economy: trust.
This story-driven course is taught by the leading experts in data science, AI, information law, science and technology studies, and responsible research and innovation, and informed by case studies supplied by the digital business frontrunners and tech companies. We will look at real-world controversies and ethical challenges to introduce and critically discuss the social, political, legal and ethical issues surrounding data-driven innovation, including those posed by big data, AI systems, and machine learning systems. We will drill down into case studies, structured around core concerns being raised by society, governments and industry, such as bias, fairness, rights, data re-use, data protection and data privacy, discrimination, transparency and accountability. Throughout the course, we will emphasise the importance of being mindful of the realities and complexities of making ethical decisions in a landscape of competing interests.
Upcoming start dates
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- Virtual Classroom
Who should attend?
General IT literacy and secondary school maths.
Course delivery details
This course is offered through The University of Edinburgh, a partner institute of EdX.
3-4 hours per week
- Verified Track -$49
- Audit Track - Free
Certification / Credits
What you'll learn
- Understand and articulate the critical, social, legal, political and ethical issues arising throughout the data lifecycle.
- Understand relevant concepts, including: ethics/morality, responsibility, digital rights, data governance, human-data interaction, responsible research and innovation.
- Identify and assess current ethical issues in data science and industry.
- Apply professional critical judgement and reflexivity to moral problems with no clear solutions.
- Evaluate ethical issues you face in your current professional practice.
- Identify and apply ethically driven solutions to those issues.
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