Lennie quickly learned that there are two types of AI: “transparent” and “black box”. With transparent AI the source code is known, and users can understand the processes that led to specific outputs.
With black box AI on the other hand the inputs and outputs may be known, but the internal workings of the system remain a mystery to the user, who has no idea how it produced certain results. Furthermore, even the creators of the black box AI may not understand how it produced those results, as machine learning can swiftly develop systems too complicated for humans to understand.
Lennie came to the realisation that for sales teams, as well as organisations at large, to ethically leverage AI, they needed to establish an ethical framework for AI governance at the highest levels of leadership. This imperative initiative demanded proactive involvement from the board of directors and C-suite executives.
He used Dr Gordon’s framework from SalesChoice as a foundation, which outlined seven ethical principles to be considered when using AI in an organisation:
-
-
- Governance
- Process
- Technology
- People
- Data & Privacy
- Transparency
- Sustainability
Subsequently, he delved into researching the ethical frameworks adopted by countries (UK, Canada, USA, China), intergovernmental organisations, (European Union, World Economic Forum, OECD, The G20) multinational technology companies (IBM, Google, SAP, Baidu), non-profit organisations (Aequitas, AI Now Institute, International Committee of the Red Cross, Women Leading in AI), and global consulting firms (PricewaterhouseCoopers, Ernst & Young, McKinsey, Deloitte).
He found satisfaction in realising that the majority of these frameworks shared common ground, yet many still exhibited deficiencies in addressing one or more of the seven principles, particularly in the realm of sustainability.
Lennie leveraged his comprehensive research in his master’s dissertation to formulate a recommendation for his organisation to develop its own ethical AI framework. Additionally, he made three sales-specific recommendations:
-
-
- Sales leaders should enhance their understanding of AI. Coupled with the adoption of transparent AI, this will foster increased trust and confidence in AI outputs.
- Sales enablement teams need skilled resources in data science, capable of designing and advancing their current AI models. These models need ongoing refinement to uphold accuracy and mitigate data drift.
- An AI Governance cross-functional strategy team should be tasked with crafting a robust AI sales enablement journey roadmap.