IIM Lucknow Research Calls for an Ethical Reset in AI-Driven Marketing
Mumbai: A new multi-institutional study involving faculty from Indian Institute of Management Lucknow argues that artificial intelligence in marketing must be governed by clearly articulated ethical frameworks if it is to deliver fair and sustainable outcomes.
The research, published in the American Business Review (an ABDC A-rated journal), examines how AI-led marketing practices affect consumers, firms, and society—and why ethical design can no longer be treated as an afterthought. Drawing on established ethical theories, the authors contend that responsible AI use is central to equity, fairness, and long-term business performance.
Real-World Failures of AI
Rather than viewing AI as a neutral abstraction, the study grounds its analysis in real-world failures. The researchers point to:
- Microsoft’s Tay chatbot, which absorbed and amplified toxic social biases when left unguided.
- The Facebook–Cambridge Analytica episode, where AI-driven data analytics enabled large-scale privacy violations.
- Amazon’s now-discontinued AI recruitment tool—found to be biased against women—illustrating how historical data can entrench inequity when deployed without safeguards.
Together, these cases underline a core risk: without strong governance, AI systems can reproduce bias, undermine trust, and erode social legitimacy.
Ethical Frameworks in AI
Co-authored by faculty from various institutions, the paper draws on utilitarianism, deontology, virtue ethics, ethics of care, and contractarianism to build a structured lens for evaluating AI in contemporary marketing.
The study identifies five ethical fault lines that demand attention:
- Monopolisation
- Privacy
- Corporate social responsibility
- Human rights
- Accountability
Through practical scenarios, the authors show how these issues emerge—and how they shape outcomes for consumers, companies, and the wider public.
Theory-Driven Solutions
To address these risks, the researchers propose theory-driven solutions:
- Advocating data democratisation to curb excessive market concentration;
- Insisting on contextual, purpose-bound data use with clear communication to consumers;
- Aligning AI deployment with international human rights standards to prevent discrimination and protect autonomy;
- Establishing robust governance mechanisms, including clearer accountability structures and ethical review processes.
Among the recommendations are institutional safeguards such as independent AI ombudspersons.
Conclusion
This research contributes to a growing global debate on how innovation can be balanced with ethical responsibility. By offering a principled framework for responsible AI in marketing, the authors position their work as a guide for academics, practitioners, and policymakers, and as a foundation for future research aimed at strengthening ethical AI adoption across markets.
