AI is transforming businesses, massively improving efficiency, scalability, and customer satisfaction. Whether they’re taking over mundane processes or creative tasks, AI systems are becoming indispensable in sectors such as financial services, entertainment, health services and transportation. But with great technological capability comes great responsibility. The use of AI opens up ethical conundrums that need to be resolved by businesses to support fairness, clarity, and transparency.
For Indian companies, dealing with the ethics of AI is especially significant. As India undergoes digital transformation, knowing how to apply AI ethically can promote trust, regulatory compliance, and growth. Below is an explainer of the top six considerations about using AI ethically.
1. Transparency and explainability
Transparency is one of the most important ethical issues in AI use. Most AI systems, especially those built on sophisticated machine learning models, are “black boxes.” That is, they make decisions but do not offer transparent explanations for how those decisions were made.
For instance, if an AI system rejects a loan application, the applicant should know why. Was it because of a low credit rating? Was it because of inadequate income? Or was the reason something else? If a customer is not able to understand the workings of an AI system that is impacting them, it can cause trust issues or legal trouble for the company.
2. Maintaining fairness
If the training datasets for AI models are biased towards certain profiles of people, the models can generate skewed results. Biased AI can end up in unfair treatment of people, particularly in sensitive domains such as legal services, recruitment and lending. For example, if an AI model is trained on past recruitment data that preferred male candidates, it could perpetuate this bias, discriminating against equally qualified female candidates.
Given that inclusivity and diversity are now central to social and economic growth, businesses need to be extra careful about biases in AI systems. Diverse and representative datasets should be used to train AI models by firms, and these systems should be audited periodically for biases.
3. Data privacy
AI technologies are dependent on huge amounts of data for effective operation, which in many cases comprises sensitive personal data. Data security and privacy are thus of utmost importance. Ethical practices entail explicit user consent, anonymisation where feasible, and strong cybersecurity to guard against breaches. Significantly, in Q3-2024 alone, more than 4220 crores of records were leaked worldwide as a result of data breaches, with the imperative need for strict data protection being underscored. With AI laws such as the EU AI Act (2024) in place abroad, and AI-specific legislation expected soon in India as well, businesses now need to stay on top of data protection regulations to avoid negative business impact.
4. Governance and accountability
When AI systems make decisions, it is difficult to establish accountability. If an AI tool gets something wrong—misdiagnoses a medical condition, for example, or approves a fraudulent transaction—who is accountable? The company that implemented the AI, the programmers who designed the algorithm, or the AI system?
For ethical AI adoption, companies need to have transparent governance structures that clearly define roles and responsibilities. Human intervention is a must, particularly in applications where AI-driven decisions have the potential to deeply affect lives and livelihoods. For example, in healthcare, although AI can help physicians diagnose illnesses, a qualified medical professional must have the final say.
5. Ethical use of AI-generated content
Generative AI technologies, which generate text, images, videos, and music, pose special ethical issues. While they provide creative potential, they can be used to create deepfakes or disinformation. This creates ethical concerns regarding authenticity, intellectual property rights, and the potential for disinformation.
Businesses that employ generative AI should promote transparency by labelling content created by AI and setting policies to avoid developing and spreading hateful or misleading information. Additionally, they must not disregard intellectual property rights and also must not apply content generated with AI that involves copyrights already created.
6. Sustaining human touch against automation
AI systems are good at automating repetitive and data-intensive tasks, resulting in greater efficiency and lower costs. Yet, automation can result in loss of jobs, which poses ethical questions regarding the social consequences of AI deployment.
In sectors like manufacturing, customer service, and data processing, companies might opt to automate jobs that were previously done by humans. Though this increases productivity, it also requires a well-considered approach to workforce management.
Conclusion
As AI technology becomes more entrenched in business processes, keeping an ethical edge in the use of AI is necessary. Businesses need to focus on the principles of transparency, fairness, and responsible use of AI in order to design systems that uphold business interests.
For Indian businesses, be it NBFCs or online marketplace companies, adopting ethical AI practices is not only a regulatory necessity but also a business imperative. Organisations that give a high priority to ethical factors while implementing AI are able to trust, build up their brand value, and serve society positively.
In summary, the use of AI ethically means making technology work for the benefit of all and ensuring that AI benefits are equally shared and utilised responsibly. Adopting best practices in ethical AI enables companies to effectively address challenges and tap the full potential of this revolutionary technology.