Data Ethics, AI and Responsible Innovation from edX

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 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.

We will engage with data-based contexts such as facial recognition, predictive policing, medical screening, smart homes and cities, banking, and AI, to explore their social implications and the tools required to minimise harm, promote fairness, and safeguard and increase human autonomy and well-being. We address cutting edge issues being grappled with by practitioners and new approaches emerging in industry and offer the opportunity for participants to develop and feedback solutions.

Completing this course will help you understand the challenges we are facing and inspire you to design, criticise, and develop better intelligent systems to shape our future.

What's inside

Learning objectives

Describe the critical, social, legal, political and ethical issues arising throughout the data lifecycle.
Explain 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.

Describe the critical, social, legal, political and ethical issues arising throughout the data lifecycle.
Explain 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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Incorporates diversity of delivery formats, including videos, readings, and discussions, to enhance engagement and cater to various learning styles

Emphasizes real-world controversies and ethical challenges, providing learners with practical insights

Led by renowned experts in data science, AI, information law, and responsible research, offering perspectives from diverse fields

Engages learners in the latest and most pressing issues in data-driven innovation, such as bias, fairness, and data privacy

Provides opportunities for learners to develop and share their own solutions to ethical challenges, fostering active participation

Covers core ethical concepts, including ethics, responsibility, and data governance, providing a solid foundation for ethical decision-making

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Ethics, AI and Responsible Innovation with these activities:

Volunteer at Ethical Data Organizations

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Make a meaningful contribution while gaining practical experience in data ethics.

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Identify non-profit organizations or initiatives working in the field of data ethics.
Contact the organizations and inquire about volunteer opportunities.
Commit to a regular volunteering schedule.

Review statistics

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Helps ground you in the core concepts that serve as the foundation for many of the topics addressed in the course

Browse courses on Data Analytics

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Review basic statistical concepts such as sampling, probability, and distributions
Work through practice problems related to hypothesis testing, correlation, and regression
Read introductory materials on supervised learning algorithms

Connect with Industry Professionals

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Expand your network and gain insights from professionals working in the field of data ethics.

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Attend industry events or conferences.
Reach out to professionals on LinkedIn or other networking platforms.
Request informational interviews to learn about their experiences and perspectives.

Eight other activities

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Review aspects of ethics and law

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Review prior knowledge and skills in ethics and law to strengthen your foundation.

Browse courses on Ethics

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Review notes and materials from previous ethics and law courses or modules.
Take practice quizzes or tests to assess your understanding.
Discuss key concepts with classmates or colleagues.

Engage in Class Discussions

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Deepen your understanding through active participation in class discussions.

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Prepare for discussions by reading the assigned materials.
Actively participate in discussions by sharing your insights and perspectives.

Experiment with supervised learning algorithms

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Provides a hands-on approach to applying your knowledge of supervised learning algorithms, giving you a deeper understanding of their strengths and limitations

Browse courses on Machine Learning

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Follow step-by-step tutorials to train and evaluate supervised learning algorithms using python libraries such as scikit-learn
Compare the performance of different algorithms on real-world datasets
Experiment with different hyperparameter settings for the algorithms to optimize their performance

Analyze Case Studies

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Apply your understanding of ethical issues by analyzing real-world case studies.

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Read and analyze case studies presented in the course materials.
Identify the ethical issues raised in each case.
Propose potential solutions and evaluate their implications.

Attend Workshops or Seminars

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Expand your knowledge and engage with experts by attending workshops or seminars on data ethics.

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Research and identify relevant workshops or seminars.
Register and attend the events.

Develop Ethical Guidelines

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Demonstrate your comprehension by creating a set of ethical guidelines for a specific data-driven technology.

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Identify the key ethical issues associated with the technology.
Research existing ethical frameworks and guidelines.
Draft a set of ethical guidelines that address the identified issues.
Seek feedback from peers or experts.

Build a data analysis dashboard

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Gives you practical experience in applying your skills to a real-world problem, demonstrating your ability to effectively communicate data insights

Browse courses on Data Visualization

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Gather data from relevant sources
Clean and prepare the data
Create visualizations and reports
Present your findings

Contribute to Open-Source Projects

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Apply your skills and contribute to the community by participating in open-source projects related to data ethics.

Browse courses on Open Source

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Identify open-source projects focused on data ethics or responsible AI.
Review the project documentation and identify areas where you can contribute.
Submit a pull request or contribute to discussions.

Career center

Learners who complete Data Ethics, AI and Responsible Innovation will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are responsible for collecting, cleaning, and analyzing data to uncover insights and trends. They may also be involved in developing and implementing machine learning models. This course would be helpful for Data Scientists who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. They may also be involved in developing and implementing data visualization tools. This course would be helpful for Data Analysts who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

See salaries and explore the career path for Data Analyst

AI Engineer

AI Engineers are responsible for designing, developing, and implementing AI systems. They may also be involved in training and maintaining these systems. This course would be helpful for AI Engineers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of AI.

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Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and implementing machine learning models. They may also be involved in training and maintaining these models. This course would be helpful for Machine Learning Engineers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of machine learning.

See salaries and explore the career path for Machine Learning Engineer

Software Developer

Software Developers are responsible for designing, developing, and implementing software applications. They may also be involved in testing and maintaining these applications. This course would be helpful for Software Developers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Computer Scientist

Computer Scientists are responsible for studying the foundations of computing and developing new computing technologies. They may also be involved in designing and implementing software applications. This course would be helpful for Computer Scientists who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Information Systems Manager

Information Systems Managers are responsible for planning, implementing, and maintaining information systems. They may also be involved in developing and managing IT policies and procedures. This course would be helpful for Information Systems Managers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Information Security Analyst

Information Security Analysts are responsible for protecting information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course would be helpful for Information Security Analysts who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Privacy Officer

Privacy Officers are responsible for developing and implementing privacy policies and procedures. They may also be involved in training employees on privacy issues. This course would be helpful for Privacy Officers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Data Protection Officer

Data Protection Officers are responsible for ensuring that organizations comply with data protection laws and regulations. They may also be involved in developing and implementing data protection policies and procedures. This course would be helpful for Data Protection Officers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Compliance Officer

Compliance Officers are responsible for ensuring that organizations comply with laws and regulations. They may also be involved in developing and implementing compliance policies and procedures. This course would be helpful for Compliance Officers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Risk Manager

Risk Managers are responsible for identifying, assessing, and managing risks. They may also be involved in developing and implementing risk management policies and procedures. This course would be helpful for Risk Managers who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Auditor

Auditors are responsible for examining and evaluating financial records to ensure that they are accurate and complete. They may also be involved in developing and implementing auditing procedures. This course would be helpful for Auditors who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Accountant

Accountants are responsible for preparing and maintaining financial records. They may also be involved in developing and implementing accounting policies and procedures. This course may be helpful for Accountants who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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Financial Analyst

Financial Analysts are responsible for analyzing financial data to make investment recommendations. They may also be involved in developing and implementing financial models. This course may be helpful for Financial Analysts who want to learn more about the ethical implications of their work. It would provide them with the knowledge and skills needed to make informed decisions about the use of data and AI.

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