In the 1940s, a company started making cooking oil in a small town in India. Today, that company, Wipro, is a giant in the tech world. It operates in 167 countries and has nearly a quarter of a million employees. The company's focus has shifted from cooking oil to IT and now to AI. Kiran Minnasandram, the VP and CTO of Wipro FullStride Cloud, is at the forefront of this shift.

        Minnasandram's role is to drive innovation and help organizations use state-of-the-art solutions. He focuses on cloud computing, which transforms how businesses operate. This includes optimizing operations, enhancing scalability, and fostering flexibility. But with great power comes great responsibility. AI ethics and sustainability are crucial for the future of IT.

        Ethical AI is about more than just following the law. It's about aligning AI with values that respect individuals, society, and the environment. Companies often struggle with AI ethics because they lack a common vocabulary and a cross-organizational strategy. They need to understand the key tenets of their AI approach and develop a risk taxonomy.

        AI adoption impacts corporate sustainability goals in both positive and negative ways. On the positive side, AI can enhance operational efficiency by optimizing supply chains and improving resource management. However, rapid AI development and deployment can increase energy consumption and carbon emissions. Training large AI models demands significant computational power, resulting in a larger carbon footprint.

        To balance AI innovation with environmental responsibility, enterprises need to establish clear policies and guidelines. They also need to track, measure, and monitor the environmental impact of AI usage. Transparency and accountability are key to driving meaningful AI innovation while being mindful of environmental commitments.

        Global regulations are evolving to address ethical AI and sustainability concerns. Existing legislation, such as privacy, consumer protection, and human rights laws, applies to AI. Some AI-specific laws are also being enacted, such as the EU AI Act. Companies need to understand how these regulations apply to AI and upskill their workforce accordingly.

        One of the biggest misconceptions about AI ethics and sustainability is that innovation and responsibility cannot go hand in hand. In reality, responsible AI is the key to long-term sustainable innovation. Companies that bring together innovation and trust will have a competitive edge.

        Wipro FullStride Cloud supports companies in aligning AI with ESG goals. They develop responsible AI frameworks and leverage AI to track and report ESG metrics. They also work on industry-specific AI solutions to meet ESG goals. Cloud solutions can reduce AI's environmental footprint by supporting energy-efficient data centers and optimizing AI model development.

        Cloud infrastructure offers powerful tools to embed ethical considerations into AI development. These tools can support bias detection, fairness testing, and secure data handling. They can also help monitor compliance with regulations and track the environmental impact of AI usage.

        Organizations struggle to measure AI's sustainability impact due to the absence of standard metrics. Cloud-based tools can help bridge this gap by offering customizable dashboards and real-time tracking tools. They can also aggregate data from multiple sources into a single view, improving transparency and decision-making.

        To improve AI transparency and accountability, organizations need to train their workforce to use AI responsibly. They also need to set up a governance structure for AI that encompasses all aspects of the business. This includes procurement, HR, CISO, and risk management.

        Bias in AI can come from several sources, including unrepresentative training data and historical prejudices. Cloud-based frameworks can help mitigate this by monitoring compliance with diverse regional regulations and ensuring fair AI model development. They can also rebalance datasets to prevent power-dynamic biases.

        Enterprises should implement governance strategies to ensure responsible AI usage. This includes having a governance framework and involving every corner of the organization. AI impact assessments are useful tools to embed legal protection, privacy, and robustness in the deployment of AI.

How to Make AI Work for Us and the Planet

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