Imagine that you are a Florentine banker in the year 1298 charged with evaluating whether or not to purchase a rival bank. Double-entry bookkeeping has not even been invented yet. The formal standards required to analyze a business do not exist. Every bank has its own unique notation and methods, making an objective assessment of your target’s finances impossible. What would you do? How could you possibly make the right decision?
This isn’t actually a hypothetical. In the year 1299, a Florentine merchant named Amatino Manucci, working for the firm of Giovannino Farofli & Company, had to evaluate the finances of the Archbishop of Aries. To accomplish his goal, Manucci invented what we today call double-entry bookkeeping and forever changed the way businesses operate.
Today, businesses continue to pursue acquisitions and mergers, just as they did in 13th century Italy. But now those acquisition targets have capabilities and business models built on data and AI. Yet traditional M&A due diligence cannot properly assess the unique risks associated with acquiring AI start-ups. It cannot reveal algorithmic discrimination or data management. It cannot even assess how a start-up’s culture might unlock (or lockdown) future value and integration success.
In short, M&A professionals in 2022 find themselves in a situation not unlike that faced by our friend Amatino Manucci. They need to evaluate M&A targets but they lack the methodology to do so.
Or, rather, they used to lack the methodology to do so. Today we are excited to join our partners in the Data & Trust Alliance in announcing its new Responsible Data & AI Diligence tool. The Responsible Data & AI Diligence tool was created for use by M&A teams in their target screening and due diligence to assess the value and risks of data, algorithms and the cultures in which they are built.
Responsible Data & AI Diligence for M&A includes three modules of acquisition criteria with guidance and education. They are:
- Responsible Culture Diligence: Suggested for the target-screening process, this module assesses a target’s mindset around data and AI and the mechanisms in place to sustain a culture of responsibility and rigor. Areas of inquiry include business purpose; values in practice; and processes to detect, mitigate and monitor data and AI issues. The module explores how the target’s teams work—for example, whether a learning mindset is incentivized and how trade-offs are made.
- Data Diligence: This module assesses how data is sourced, used, and responsibly governed, in order to understand its true value and utility for an acquirer and whether any mitigation is required. It inquires into data quality, data bias, data consent and rights, including third-party usage rights.
- Algorithmic Diligence: This module assesses the design, deployment and monitoring of algorithmic models to ensure they perform as intended and minimize unintended consequences. It includes inquiries into a target’s approach to sourcing and managing training data, explainability, robustness, fairness, performance monitoring and independent audits.
These modules supplement an organization’s existing technology, privacy and security diligence. The tool is designed to be used in its complete form and be adapted to fit company acquisition and deal strategy and objectives. More than 80 experts contributed to the development of Responsible Data & AI Diligence for M&A. First, a cross-Alliance team of member company experts and external specialists in AI ethics and policy, AI risk, legal and compliance, data quality and diligence, and mergers and acquisitions came together to create the new criteria and associated education and guidance. The work was then tested and refined with input from additional Alliance member company experts and external leaders in corporate development, data, AI and technology ethics.
Diveplane is the leading developer of Understandable AI® in the world and our business is based on the belief that understandability is the key requirement for businesses seeking to apply AI to mission-critical processes. Only Understandable AI can be applicable, auditable, and ethical when human lives are at stake.
As our co-founder and CEO, Dr. Michael Capps, explains, “the goal of the Alliance is the widespread adoption of ethical data and AI practices, which is why Diveplane is so proud to play an active role. This Diligence work will help acquirers make safer M&A decisions, help private equity make savvier investment decisions, and help companies like ours build more responsible data culture and practices.”
With AI becoming an evolving part of every business, it’s possible that these new standards might become just as important for M&A in the 21st century as double-entry bookkeeping was for Florentine merchants in the 14th century.
For more information, be sure to check out the official press release, which has additional information on the Data & Trust Alliance and the companies that have contributed to the tool.