Navigating the ethical minefield of the AI landscape- Intel's Santhosh Viswanathan on what India should do

tech.hindustantimes.com:

The remarkable strides in artificial intelligence (AI) have opened up unprecedented possibilities, impacting virtually every facet of our lives. What was once a realm reserved for specialised experts has now become accessible to individuals worldwide, who are harnessing AI's capabilities at scale. This accessibility is revolutionising how we work, learn, and play. 

While democratising AI heralds the limitless potential for innovation, it also introduces considerable risks. Heightened concerns over misuse, safety, bias, and misinformation underscore the importance of embracing responsible AI practices now more than ever.

Derived from the Greek word ethos which can mean custom, habit, character or disposition, ethics is a system of moral principles. The ethics of AI refer to both the behaviour of humans that build and use AI systems as well as the behaviour of these systems.

For a while now, there have been conversations – academic, business, and regulatory – about the need for responsible AI practices to enable ethical and equitable AI. All of us stakeholders – from chipmakers to device manufacturers to software developers – should work together to design AI capabilities that lower risks and mitigate potentially harmful uses of AI. 

Even Sam Altman, OpenAI's chief executive, has remarked that while AI will be “the greatest technology humanity has yet developed”, he was “a little bit scared” of its potential. 

Responsible development must form the bedrock of innovation throughout the AI life cycle to ensure AI is built, deployed and used in a safe, sustainable and ethical way. A few years ago, the European Commission published Ethics Guidelines for Trustworthy AI, laying out essential requirements for developing ethical and trustworthy AI. According to the guidelines, trustworthy AI should be lawful, ethical, and robust. 

While embracing transparency and accountability is one of the cornerstones of ethical AI principles, data integrity is also paramount since data is the