From Algorithms to Accountability: How AI is impacting corporate governance (1/2)
Bhawna Sachdeva K.
Strategic Leader Driving Market Expansion & Sustainable Growth | Expert in P&L Management, Team Leadership & Operational Excellence | Transforming Challenges into Opportunities for Over 15 Years
A random quick chat with my app-based taxi driver, made me realize it an algorithm that is responsible to send bookings to drivers. In short – its AI at work!
Further, he highlighted how there is an element of bias in such allocations. Of course, many of such perspectives are debatable but this got me thinking how AI is impacting good corporate governance and why businesses need to rethink how they manage their operations in sync with AI.
AI is changing how companies make decisions, manage risks, and handle day-to-day activities. Because of this, conventional corporate governance structures need to evolve.
Here are the key reasons why businesses must adapt:
Accountability and transparency in AI systems - AI systems often make decisions using complex algorithms, which can be difficult to understand. Traditional governance needs to adapt by ensuring these AI-driven decisions are clear and easy to explain. This could involve using techniques like Explainable AI (XAI) (in love with this concept!!!), which makes AI decisions more understandable
Reducing bias and ensuring fairness - AI systems can sometimes reinforce biases present in the data they are trained on, leading to unfair decisions in areas like hiring, customer service or as we discussed, task allocation. To prevent this, businesses should focus on the use of techniques that detect and reduce biases.
Data management and security - AI relies heavily on data, so managing that data properly becomes crucial. Traditional data governance needs to be upgraded to ensure data quality and security. Companies must adopt advanced data protection methods like encryption and privacy-preserving techniques.
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Managing AI risks and validating models - AI introduces new risks, including errors, security threats, and ethical concerns. Businesses must go beyond basic risk management to continuously assess and validate AI models. This includes regularly testing AI systems, ensuring they meet ethical standards, and addressing any emerging risks.
Ethics and values in AI - Companies must embed ethical considerations into their AI governance. This means setting standards for responsible AI development and ensuring that ethical issues are considered throughout the entire AI process, from data collection to decision-making. Imagine AI signing the ethics bond!
Aligning AI with Stakeholder Interests - Finally, businesses need to ensure that their AI systems consider the needs of all stakeholders. This includes allowing humans to intervene in AI-driven decisions, especially in high-risk situations. Governance frameworks should support the integration of human judgment with AI to ensure ethical, legal, and fair decision-making.
As I studied more; I came across interesting examples on how some of India’s leading companies are already working actively to adapt governance structured to AI. Let's keep that discussion for next time!
Insightful!