Recent advances in computing may place us at the threshold of a unique turning point in human history. Soon we are likely to entrust the management of our environment, economy, security, infrastructure, food production, healthcare, and to a large degree even our personal activities, to artificially intelligent computer systems.

The role of Facebook’s “Free Basics” in Myanmar genocide and the Cambridge Analytica fiasco are only some of the dire situations where data has been exploited for horrendous activities. The blame game is only a part of post-mortem. The policy changes usually take place as a face-saving manoeuvre.

It is therefore extremely crucial for the key players in AI and also for the aspirants to have an education imbued with the awareness of responsibilities that come with such expertise.

The prospect of handing over the keys to increasingly autonomous systems induces paranoia in people thanks to pop sci-fi. How will society respond as versatile robots and machine learning systems displace an ever-expanding spectrum of blue- and white-collar workers? Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few? How can we ensure that these systems respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend? What, if any, legal rights and responsibilities should we grant them? And should we regard them merely as sophisticated tools or as a newly emerging form of life?

Here are a few top courses offered by the likes of MIT and Stanford in their effort to induce accountability in deploying machines.

Data Science Ethics By University Of Michigan

This course provides a framework to analyse these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. And, examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the “right to be forgotten.”



This course will help answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair.



Data scientists and anyone beginning to use or expand their use of data will benefit from this course. No particular previous knowledge needed.

Check here for more information.

Responsible Innovation In The Age Of AI By IEEE

This course focuses on how traditional philosophical models like utilitarianism, virtue ethics and other key modalities of applied ethics have evolved to embrace specifics of algorithmic tracking and intelligence augmentation of AI. This course shows that by implementing these new models, businesses can learn how to holistically incorporate AI into their innovation process to sustain profits while honouring their purpose. This course also features recommendations on who within an organization should be tasked with exploring AI Ethics to implement these ideas.

Check here for more information.

Level: Introductory

Ethics And Law In Analytics and AI By Microsoft

This course will help learn to apply ethical and legal frameworks to initiatives in the data profession. You’ll explore practical approaches to data and analytics problems posed by work in Big Data, Data Science, and AI. And, investigate applied data methods for ethical and legal work in Analytics and AI.

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

Check here for more information.

The Ethics And Governance of AI by MIT

This course will pursue a cross-disciplinary investigation of the development and deployment of the opaque complex adaptive systems that are increasingly in public and private use. While helping explore the proliferation of algorithmic decision-making, autonomous systems, and machine learning and explanation; the search for balance between regulation and innovation; and the effects of AI on the dissemination of information, along with questions related to individual rights, discrimination, and architectures of control.

Check here for more information.

The Economic Advantage Of Ethical Design By IEEE

This course covers in detail, the rapid growth of autonomous and how intelligent technology is affecting large portions of society in multiple verticals all at the same time. AI/S technology cannot be built in isolation, and to get a full sense of ethical and policy impacts of this technology it’s essential to understand the larger context of its implementation to best increase societal well-being while building your business.

Check here for more information.

Additional Learning Resources Available Online

The above courses introduce the enthusiast to the sophistication that comes with deploying machines and the future of humans’ in the world of AI or vice versa.

Stanford’s Artificial Intelligence – Philosophy, Ethics, and Impact course one of the foremost courses launched in this domain. The goal of this course is to equip students with the intellectual tools, ethical foundation, and psychological framework to successfully navigate the coming age of intelligent machines.Though this course needs to get an update on 2018-19, the coursework from 2014 definitely acts as a kickstarter for those who are interested.

Check here for more information.

Dive deep into AI ethics, governance and policy-making with the following reading list and acclaimed fellowship programs:

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