Introduction

Over the years the world has witnessed a widespread adoption of AI due to its success across multiple sectors. However, with widespread adoption comes the possibility of misuse or nonadherence to societal norms. Keeping this in mind, the handbook has been published by GIZ in July 2021, which will act as a practical guiding document that helps in the development of AI technologies that are legally and socially acceptable. It lays down the rules and best practices on the ethical use of AI.

The handbook will come in handy for AI developers as it will give them a clear understanding of the important ethical frameworks and the issues related to protection of personal data and privacy. By adhering to the parameters pointed out by the handbook, developers can avoid unnecessary complications that may arise in the future due to their limited understanding of definition ethics. The handbook encourages developers to think from a societal point of view when designing the product rather than solely focusing on algorithmic accuracy.

 

Relevance of the Report

At a time when the integration of AI into various aspects of human life is underway, there are increasing instances of biases in AI mainly due to unconscious biased programing by developers or absence of historical data to train AI, that represents whole population fairly. In addition to this, the other ethical concerns often faced are privacy and surveillance and the role of human judgement. Hence, it has become of paramount importance to train members of AI community on ways which will enhance societal benefits. The first step towards this is designing a handbook that will act as a guideline for the community, including the developers.


Key Takeaways

  • The handbook discusses key concepts like bias, privacy, data security, transparency and accountability
  • It also highlights the best practices, checklists and citations to provide an actionable understanding of the topic
  • The ethical principles are clearly mentioned and in line with the principles proposed by the OECD and NITI Aayog
  • Finally, it encourages and provides guidelines for developers to think beyond algorithmic accuracy and look the lens of social impact and accountability

Want to publish your content?

Submit your case study and share your insights to the world.

ALSO EXPLORE

DISCLAIMER

The information provided on this page has been procured through secondary sources. In case you would like to suggest any update, please write to us at support.ai@mail.nasscom.in