Developing a Practical Model for Ethical AI in the Business World: Introduction

As we head into 2020, the concept of “AI (Artificial Intelligence) for Good” is becoming an increasingly common phrase. Individuals and organizations with AI skillsets (including data management, data integration, statistical analysis, machine learning, algorithmic model development, and application deployment skills) have effort into pursuing ethical AI efforts.

Amalgam Insights believes that these efforts have largely been piecemeal and inadequate to meet common-sense definitions for companies to effectively state that they are pursuing, documenting, and practicing true ethical AI because of the breadth and potential repercussions of AI on business outcomes. This is not due to a lack of interest, but based on a couple of key considerations. First, AI is a relatively new capability in the enterprise IT portfolio that often lacks formal practices and guidelines and has been managed as a “skunkworks” or experimental project. Second, businesses have not seen AI as a business practice, but as a purely technical practice and made a number of assumptions in skipping to the technical development that would typically not have been made for more mature technical capabilities and projects.

In the past, Amalgam Insights has provided frameworks to help organizations take the next step to AI through our BI to AI progression.

Figure 1: Amalgam’s Framework from BI to AI




To pursue a more ethical model of AI, Amalgam Insights believes that AI efforts need to be analyzed through three key lenses:

  • Executive Design
  • Technical Development
  • Operational Deployment

Figure 2: Amalgam’s Three Key Areas for Ethical AI

In each of these areas, businesses must ask the right questions and adequately prepare for the deployment of ethical AI. In this framework, AI is not just a set of machine learning algorithms to be utilized, but an enabler to effectively augment problem-solving for appropriate challenges.

Over the next week, Amalgam Insights will explore 12 areas of bias across these three categories with the goal of developing a straightforward framework that companies can use to guide their AI initiatives and take a structured approach to enforcing a consistent set of ethical guidelines to support governance across the executive, technical, and operational aspects of initiating, developing, and deploying AI.

In our next blog, we will explore Executive Design with a focus on the five key questions that an executive must consider as they start considering the use of AI within their enterprise.