Embracing responsible AI practices: Its impact in streamlining and improving efficiencies across sectors through data debiasing and inclusion

By Devesh Raj, Director – AI Center of Excellence (CoE) and Data Science Practice Lead, Fidelity Investments India

At one time, AI used to be the territory of an exclusive set of large global technology firms, that had access to large data sets and the AI technology to work with such large data sets to derive meaningful insights and develop solutions in their areas of work. With the explosion of generative AI in the recent past, especially with tools like ChatGPT, the barrier to entry for the use of AI by firms has been significantly lowered, leading to the potential for more widespread adoption of AI by companies across sectors in their decision-making and solutions.

The case for responsible AI
The situation today is evolving at warp speed, as AI becomes a lot more mainstream and companies across the board take to it more rigorously, owing to FOMO (the fear of missing out). AI’s potential to enable decision-making at scale, detect errors in processes, and predict the future makes it a must-have tool for enterprises to have a competitive edge. AI has paved the way for increased digitalisation and the use of technology-enabled products across sectors. However, owing to the rapid pace of change in this space, the AI boom faces us with several challenges, including unreliable data, data privacy concerns, inherent biases of various kinds, the lack of traceability, non-inclusion of all segments of society, lack of transparency, and more.

One of the biggest of these challenges that we face with the unregulated explosion of AI is the potential for biases to percolate across AI systems, which, if unchecked, will be difficult to address, especially as things move so fast. Inherent biases that creep in could lead to the amplification of existing societal biases, discrimination against and non-inclusion of certain groups, and unfair decision-making. However, biases can be avoided if companies practice the use of diverse and inclusive data sets, perform rigorous testing, and monitor their systems for fairness. By actively working to minimise biases and unfairness, organisations can ensure that AI technologies are inclusive and serve the best interests of all users and stakeholders.

Hence, it is becoming highly imperative for the industry across sectors to come together quickly to formulate widely accepted rules, regulations, and ethical frameworks for the use of AI in a responsible manner. This will help to not only regulate and ensure the responsible use of AI but also to explore the potential of AI to benefit society.

How responsible AI can benefit society
When implemented responsibly, AI holds tremendous potential to benefit society. It is essential for companies to acknowledge this potential and embrace responsible AI practices to drive positive change. The key tenets I see for the responsible use of AI are fairness, reliability, privacy, explainability, and inclusivity. Working on these principles, organisations can guide the far-reaching power of AI to benefit society in various ways.

With great power comes great responsibility.” Here are some potential use cases that I see:
 Debiasing Data: Responsible AI enables organisations to identify and address biases in data, leading to more inclusive decision-making processes. This would help them identify the diverse needs of various underserved social segments and develop solutions to benefit
them.

 Enhancing Efficiency and Productivity: AI systems can optimise operations, streamline processes, and improve productivity across industries. This has the potential to generate economic growth and create new employment opportunities.
 Advancing Driverless Technology: Responsible AI is key to developing safer and more reliable autonomous vehicles. This technology can significantly reduce the number of
accidents and enhance transportation efficiency.
 Reinforcement Learning Applications: Responsible AI can enhance reinforcement learning techniques, allowing for more effective problem-solving and decision-making in areas such as robotics, healthcare, and education.
 Fair Loan Distribution: AI can help identify promising startups in less-privileged nations by matching the profiles of their founders with similar profiles in wealthier nations. This can enhance access to capital for startups in disadvantaged regions.

Embracing responsible AI practices is not only an ethical imperative but can also provide
organisations with a strategic advantage. By adopting the principles of responsible AI—fairness, reliability, privacy, explainability, and inclusivity—companies can unlock the immense potential of AI to benefit society at large. Collaboration among industry stakeholders, the establishment of clear regulations and guidelines, and the integration of responsible AI principles into organisational strategies will pave the way for a future where AI-driven solutions can greatly contribute to the progress and upliftment of all sections of society.