Page 38 - Banking Finance December 2024

ARTICLE

Ethics in Artificial

Intelligence:

Navigating the

Namita Mishra
Future Responsibly Faculty at ULA-Operational
Senior Manager

Excellence
Union Bank of India

Ethics in AI encompasses a wide range of issues, including fairness, accountability, transparency,
and the potential for bias. At the core of these discussions lies the question: How do we ensure
that AI serves humanity rather than undermines it? As AI systems increasingly influence critical
areas such as healthcare, finance, and law enforcement, the stakes are high.

A s we stand on the brink of an era defined by in AI algorithms. These systems learn from vast datasets,
artificial intelligence (AI), the ethical implications
and if those datasets reflect historical inequalities or
of these technologies have emerged as a crucial
conversation. The rapid advancements in AI capabilities prejudices, the algorithms can inadvertently perpetuate and
amplify these biases. For instance, a hiring algorithm trained
present us with extraordinary opportunities, but they also on biased data may favor candidates from certain
pose profound moral questions. From self-driving cars to demographics while unfairly disadvantaging others. It is
decision-making algorithms, the impact of AI is pervasive, imperative that developers employ rigorous testing and
challenging our understanding of ethics in technology. validation processes to ensure fairness in AI outcomes.

Accountability and Transparency
The Ethical Landscape
As AI systems become more autonomous, determining
Ethics in AI encompasses a wide range of issues, including accountability becomes increasingly complex. When an AI
fairness, accountability, transparency, and the potential for makes a decision that leads to harm or error, who is
bias. At the core of these discussions lies the question: How responsible? Is it the developer, the user, or the organization
do we ensure that AI serves humanity rather than that deployed the technology? Establishing clear
undermines it? As AI systems increasingly influence critical accountability frameworks is essential to navigate these
areas such as healthcare, finance, and law enforcement, the dilemmas. Moreover, transparency in AI decision-making
stakes are high. Misaligned ethical standards can lead to processes can help build trust. Stakeholders must understand
devastating consequences, including perpetuating inequality how AI systems arrive at their conclusions, especially in high-
and infringing on individual rights.
stakes scenarios like criminal sentencing or medical diagnoses.
Fairness and Bias Privacy Concerns
One of the most pressing ethical concerns is the issue of bias The integration of AI in daily life raises significant privacy

34 | 2024 | DECEMBER | BANKING FINANCE