AI Ethics and Transformations (Free)

Gunjan is joined by Stephanie Kelley to discuss the importance of considering AI ethics during transformations. Watch the video below and read Stephanie's guide to an ethical AI transformation below the video.

So what is artificial intelligence ethics and why does it matter for my digital transformation?

By Stephanie Kelly, April 2020

Artificial intelligence (AI) ethics at its most basic level is how your organization is using the technology, and whether your stakeholders (employees, customers, the public, etc.) believe it is being used in a trustworthy way. Most organizations undergoing digital transformation are doing so to achieve a strategic objective; whatever that may be, AI is often adopted as a tool to help achieve this. AI ethics becomes a responsibility of any organization adopting AI in their digital transformation, no matter how complex or simple their use of the technology is. Not only is it an organizational responsibility, but also a clear expectation customers, and organizations will be at risk of loosing customer trust if they are using AI without the proper ethical oversight. AI ethics is no longer an exclusive priority for data scientists, today, AI ethics needs to be a priority for all business leaders.

A quick-start guide to an ethical AI digital transformation:

1. Develop principles first: Gone are the days were an organization can test the waters with customer data; privacy, transparency, and accountability are some of the key priorities in this fourth industrial revolution, and your customers expect you have a well-aligned list of ethical principles prior to undertaking any AI-related projects.

2. Test-test-test: Your organization can then pick 3-4 diverse AI projects to test the principles out on; where possible, ensure these tests are done in sandboxes and/or with artificial data to protect customers and employees during this learning phase. Revise your AI ethics principles as needed based on the ethical discussions and outcomes of these tests.

3. Translate your principles into process: Once you've aligned on a first draft of principles, adapt them into a consistent process to be used for every AI project. This could be in the form of an ethical checklist completed by your project leads, an automated dashboard, or could added to existing privacy, regulatory, or compliance processes, depending on your industry.

4. Start today: No matter where you are in your AI digital transformation journey, it's not too early or too late to add in ethical oversight to the initiative.

5. Interested in developing an AI ethics principles for your organization or area group? Check out my research to see A Template for an AI Ethics Code of Conduct.

What else to keep your eye on?

AI as a Service (AIaaS) - AI (and other analytics) services are performed by third parties which allows an organization to experiment with AI without a large initial investment in technology or data science resources. Combined with existing AI platforms such as Azure, IBM Watson, or DataRobot, AIaaS will allow more organizations to test how they can use AI to meet their strategic objectives with fewer digital transformation requirements. Some of these organizations have ethical principles and frameworks, but many do not, and it's important for your organization to have clear ethical AI principles and a consistent process when working with AIaaS vendors to maintain customer trust and prevent ethical AI issues.

Want to learn more about an ethical AI digital transformation? Check out my blog: Ethical AI for Organizations.

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