Ethics Audits for AI-Powered Business Valuations: A Critical Necessity in the M&A Sector

In the rapidly evolving world of Mergers & Acquisitions (M&A), AI-powered tools are playing an increasingly important role in business valuations. However, the use of these technologies also brings new ethical challenges that require careful scrutiny. Ethics audits for AI systems in the M&A sector are therefore gaining significance to ensure fair and transparent valuation processes.

The Necessity of Ethical Reviews in the AI-Supported M&A Landscape

AI systems used in M&A transactions can exhibit various types of biases that may lead to unfair or distorted valuations. Anchoring bias, confirmation bias, and overconfidence bias are just a few of the pitfalls that can be embedded in AI algorithms¹. These biases can not only result in misjudgments of company value but also raise ethical questions, especially when considering factors such as diversity, sustainability, or social responsibility.

To address these challenges, experts like Prof. Dr. Kerstin Schlögl-Flierl and Alina Lorenz from the University of Augsburg are developing concepts for ethical audits of AI applications². These audits aim to evaluate AI systems not only technically but also ethically, identifying and assessing risks at all stages of AI development and application³.

Certification Systems for Fair AI Valuation Models

Developing certification systems for fair AI valuation models is a complex undertaking. The initiative TRUST YOUR AI, founded by Know-Center, SGS, TU Graz, and the University of Graz, has produced a whitepaper addressing how the fairness of AI applications can be independently assessed and certified⁴.

Such a certification system would need to consider various aspects, including:

1. Ethics and Law: Does the AI application respect societal values and legal requirements?
2. Autonomy & Control: Is self-determined, effective use of the AI possible?
3. Fairness: Does the AI treat all stakeholders fairly?
4. Transparency: Are the AI’s functions and decisions comprehensible?
5. Reliability: Does the AI operate reliably and robustly?
6. Security: Is the AI protected against attacks, accidents, and errors?
7. Data Privacy: Does the AI safeguard privacy and other sensitive information?⁵

Implementing Ethics Audits in Practice

Conducting ethics audits for AI-supported business valuations requires an interdisciplinary approach. Experts from technology, ethics, business, and law must collaborate to develop comprehensive audit procedures³.

Companies using AI systems for M&A valuations should commission regular external AI audits to ensure transparency and fairness⁶. These audits can help uncover potential biases and recommend corrective measures.

Conclusion

Ethics audits for AI-supported business valuations are not only a technical necessity but also an ethical obligation. They help build trust in AI systems within the M&A sector and ensure fair, transparent valuation processes. While the development of comprehensive certification systems is still in its early stages, it is equally important for companies and regulatory bodies to proactively contribute to shaping ethical standards for AI in the financial world.

Footnotes

1. https://www.drkarlpopp.com/karl-michael-popps-blog/which-types-of-bias-occur-during-negotiations-in-mergers-and-acquisitions-rbfr5 ↩

2. https://www.zww.uni-augsburg.de/news-details/ethische-audits-fuer-ki-verantwortung-in-der-technologiegestaltung.html ↩

3. https://www.zww.uni-augsburg.de/wir-feiern/ethische-audits-bei-ki-anwendungen.html ↩ ↩²

4. https://dataintelligence.at/kann-man-die-fairness-einer-ki-zertifizieren/ ↩

5. https://www.ki.nrw/flagships/zertifizierung/ ↩

6. https://zvoove.de/wissen/blog/ki-und-ethik-so-meistern-unternehmen-ethische-herausforderungen ↩