Combining Purpose And Outcome To Understand AI’s Impact
The Artificial Intelligence Trust Quotient Series, Part Five: Purpose & Outcome
To state that the purpose and intended outcome of an AI-powered solution is critical to building trust in it, seems obvious. That’s because it is. But quantifying the nature, scale and impact of an AI powered solution is - to say the least - tricky. Recent advances in legislation help highlight this point, with the new EU AI guidelines amongst the first in the world to attempt to bring this into a more detailed, regulatory framework.
The purpose of the Artificial Intelligence Trust Quotient (AI-TQ) is to help non-technical business stakeholders understand and therefore decide their level of trust in AI-powered solutions means it must consider the imperative driving the use or development of those solutions. Introducing the assessment areas of Purpose and Outcome, the AI-TQ is trying to help its audience navigate what is potentially a complex topic; and, one in this case that may be shrouded in an additional technical language, law.
Purpose + Outcome = Impact
I believe it’s fair to say that both these areas of assessment, Purpose and Outcome, are so significant they warrant their own, dedicated coverage. So why combine them?
Together, Purpose and Outcome are more than the sum of their parts, I think of it as being similar to a simple equation. For example, if the purpose is commercial, say tailored advertising, and the outcome’s scope is limited to offering a small discount for a product or service then the result of that equation, the impact, is likely quite limited. At the other end of the scale, perhaps the purpose is making decisions about an individual’s entitlement to a form of life-extending healthcare which would have an impact immeasurably greater.
Serving A Commercial Or Civil Purpose
As with most forms of assessment, it is possible to substantially overcomplicate what defines the purpose of an AI-powered solution. To keep things simple, the AI-TQ splits purpose into two broad areas:
Commercial - commercial purposes will be focused on the generation of revenue, management of costs, or to meet compliance and risk management requirements in the private sector.
Civil - civil purposes will be focused on improving the services and outcomes delivered and sought by public sector (state, federal, local government and related organizations) bodies.
Without judgment, it is important to note that AI solutions used for purposes that include military, battlefield and other defense activities funded by either / or private or public organizations are specifically out-of-scope for the AI-TQ.
Outcome Requires Additional Perspectives
Different outcomes and decisions have different magnitudes of impact, impact on different groups or categories, and may, or may not be automated. The AI-TQ seeks to assess the type of outcome in terms of the Purpose variable, whether it is commercially or civilly focused, and impacts an individual, a group, or an organization.
The framework also assesses the nature of the outcome. This is relatively simplistic in a determination as to whether the outcome is reversible or not.
Automation is also a factor in the outcome. If the outcome is automated, with no obvious route to review or monitoring for erroneous output covered by the “Human Governance” assessment area of the AI-TQ.
Individual
Low Scale of Impact, e.g. automated personalization of web content.
Medium Scale of Impact, e.g. automated tailoring of service offering.
Highest Scale of Impact, e.g. automated decision making with high degree of impact on subject’s outcomes.
Groups
Low Scale of Impact, e.g. automated personalization of web content.
Medium Scale of Impact, e.g. automated tailoring of service offering.
Highest Scale of Impact, e.g. automated decision making with high degree of impact on subject’s outcomes.
Organization
Low Scale of Impact, e.g. automated personalization of web content.
Medium Scale of Impact, e.g. automated tailoring of service offering.
Highest Scale of Impact, e.g. automated decision making with high degree of impact on subject’s outcomes.
How users of the AI-TQ choose to define low, medium, and highest impacts will, of course, be open to interpretation. In combination with other assessment areas, such as “Values” and “Human Governance” it is the aim of the AI-TQ to provide an overall assessment that combines different perspectives on the technology in question.
Coming Next To The AI-TQ: Personal Characteristics
This research is part of a series that will culminate in the official launch of the Artificial Intelligence Trust Quotient (AI-TQ) assessment. Next in the series is “Personal Characteristics” - perhaps one of the most hotly-debated subjects within the AI arena, an examination of the use of data in AI-powered solutions that helps identify us.
Also, my continued thanks and appreciation for the feedback and comments on this research so far! It is immensely valuable to me, and I look forward to more.
