Artificial Intelligence (AI) and Machine Learning (ML) is transforming industries and solving important and real-world challenges at a scale. The technology is maturing rapidly with seemingly limitless applications. These vast openings carry with it a deep responsibility to build AI that works for everyone.

AI applications have demonstrated its ability to automate daily works while also augmenting human capacity with new insight. However, with great power comes great responsibility. The fear of workforce displacement, loss of privacy, potential biases in decision making and lack of control over automated systems and robots are some of the menacing possibilities. Artificial intelligence technologies in the commercial and public sector like autonomous cars, chatbots take over the tough human labor process by packing and endlessly answering human queries. However, the downside is that an autonomous car could cause an accident and a chatbot might learn to use offensive languages. These possible incidents have stoked fears of a ‘job apocalypse’ that concerns over inclusion, diversity, privacy and security.

As the usage of AI and ML increases, technology is becoming more pervasive. Technology is taking part in an increasing number of decisions like benefit payments, mortgage approvals, and medical diagnosis. When AI becomes a part of every working system, transparency and visibility disappears. One of the major threats that AI might imply is reinforcing existing human biases. These biases are unidentified and come about due to a lack of diverse perspective when developing and training the system.

In addressing all these issues and furthermore, Responsible AI/ML offers a way for everyone to adopt a ‘people first’ approach that is fair, accountable, honest, transparent and human-centric.

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