AI systems are evolving at neck-breaking speeds. They aren’t just handling human tasks more efficiently, they also take on responsibilities that we can’t do. Such roles include providing relevant and instant recommendations to consumers or reviewing and approving hundreds of bank transactions at once. Moreover, there’s a growing need for automated systems to help industries navigate through fresh data and new methods of using data.
Engendering Trust: A Two-Fold Task
Building trust in AI is two-pronged—it involves selecting a trustworthy solution and cultivating a culture of user trust in AI.
Choosing Trustworthy AI
You can use the following as performance indicators for your AI:
· Explainability
Knowing exactly how the AI system works and produces results is a primary step to buy-in. When you can understand the process, it’s easier to relay its benefits to your company’s decision-makers and end-users.
· Security
Your solution should ensure the security of users’ personal data from the training phase to actual production. It should offer protection against unauthorized use, access, modification, disclosure, and destruction.
· Reliability and Speed
You become more confident about the reliability of your AI solution if you know that it has passed industry standards. It should also be able to quickly produce insights or predictions.
· Objectivity
The AI system should use data that hasn’t been falsified or corrupted. It shouldn’t also show bias toward privileged groups or individuals (particular gender or nationality).
· Robustness
Robust solutions are capable of operating accurately and resiliently amid different conditions. It should have safeguards that can prevent or reduce harm during adversarial attacks.
Teaching Teams to Trust AI
AI-enabled software and other technologies can now substitute humans for many tasks, from speech recognition, visual perception, language translation, and decision making. But users need to understand what state-of-the-art AI can and can’t do to be able to accept and trust its decisions. A recent study by Rackspace supports this point: 62% of IT leaders from different industries said their organizations consider AI investment a high priority. However, 36% of respondents said that proving AI’s business value is their most common challenge.
How can you then encourage your team to trust in AI?
1. Invest in general and specialized education.
Executives and teams need to understand the different applications of AI and how they will benefit. Share the criteria you used to evaluate its trustworthiness. Then describe how you’re embedding AI in existing systems. You should clarify whether AI integration will entail changes or create entirely new workflows.
You can also improve trust in AI within your organization by hiring people with the skills to maintain and manage AI-run systems. These AI specialists or your chief information officer can then explain how AI can provide insights for better decision-making. When managers and team heads understand how AI reached predictions, it will be easier to accept the credibility of its output.
2. Set up a feedback mechanism.
Regularly engage your team for feedback about the usefulness and output of your AI systems. Create a form or questionnaire assessing the performance of your AI solution and let your team answer. You can feature the indicators discussed above to gauge your colleague’s sentiments about how AI improves productivity and speeds up decision-making. Acknowledge their inputs and see how your IT team or AI solution provider can address issues.
3. Take a holistic approach to AI application.
Leaders who tapped AI to simultaneously tackle decision-making, system modernization, and business transformation saw a 36% AI adoption rate in their organizations, according to a PwC survey. The extent of adoption was lower (20%) in businesses where owners adopted AI on a piece-meal basis.
