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The Business of AI: Responsible AI

Posted by Jason Richards on Dec 22, 2020 1:00:00 PM

The societal implications of AI and the responsibility of organizations to identify and reduce unintended consequences of AI technology are significant. Considering this responsibility, organizations are finding it necessary to create internal policies and practices to guide their AI efforts, whether they are deploying third-party AI solutions or developing their own.

AI is the defining technology of our time. It is already enabling profound progress in nearly every field of human endeavor and helping to address some of society’s most pressing challenges. In order to get a better understanding of where responsible AI needs to be addressed, we need to take a look at some implications surrounding the subject.



Six Practical Implications of Responsible AI

Societal implications of AI

How do we design, build, and use AI systems that create a positive impact on individuals and society? How can we best prepare workers for the impact of AI? How can we attain the benefits of AI while respecting privacy?

The importance of a responsible approach to AI

Our responsibility to make a concerted effort to anticipate and mitigate the unintended consequences of the technology we release into the world through deliberate planning and continual oversight.

Novel threats

Prepare for new types of attacks that influence learning datasets, especially for AI systems that have automatic learning capabilities.

Biased outcomes

Another unintended consequence that organizations should keep in mind is that AI may reinforce biases without deliberate planning and design.

Sensitive use cases

Society has a responsibility to set appropriate boundaries for the use of these technologies, which includes ensuring businesses, governments, NGOs, and academic researchers use of facial recognition technology remains subject to the rule of law.

Applying these ideas in your organization

The following three questions can help you start to consider the ways your organization can develop and deploy AI in a responsible manner.

  1. How can you use a human-led approach to drive value for your business?
  2. How will your organization’s foundational values affect your approach to AI?
  3. How will you monitor AI systems to ensure they are evolving responsibly?

Now that we have a better understanding of the concepts surrounding responsible AI we can utilize guiding principles to steer our technology to be responsible.



Guiding Principles

Fairness AI systems should treat everyone fairly and avoid affecting similarly situated groups of people in different ways.

Reliability and safety — To build trust, its critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions.

Privacy and security With AI, privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions and decisions about people.

Inclusiveness Everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of human needs and experiences. It should recognize exclusion, solve for one and extend to many and learn from diversity.

Transparency When AI systems are used to help inform decisions that have tremendous impacts on peoples lives, it is critical that people understand how those decisions were made.

Accountability — The people who design and deploy AI systems must be accountable for how their systems operate.

Organizations should also consider establishing a dedicated internal review body. Every individual, company, and region will have their own beliefs and standards that should be reflected in their AI journey. This is just one perspective; consider developing your own guiding principles.

The approaches shown in this article are extremely high-level overviews of the process. To get in-depth information, try some of Fast Lane’s Digital Services & Artificial Intelligence courses!

Topics: AI/IoT/DX, business

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