We have recently accepted the idea of omnipresent AI adoption, but new changes and technology reshaping are already on the doorstep. Have you heard of the Responsible AI concept? Let’s take a closer look at it, since it will soon become a mandatory tool to build business relationships.
Proofs of Concept are in trend now
Enterprises usually struggle to develop AI pilots into production. Unfortunately, many solutions, when facing approval and development obstacles, never overgrow the “Proof of Concept” stage. You might encounter such a situation too. Being concerned about disruptive effect of innovations, most businesses just try them out in a few cases and do not go further. Thus, robots are trusted to make the first lead touch only, with all other steps being usually assigned to a human being. This is why such robots are not expected to do more than read, write, speak, and copy/paste.
In such circumstances, the value and business potential of AI cannot be unveiled and win the so much needed customer confidence. Meanwhile, AI-based solutions can completely change the approach to working, training employees, ensuring people safety, as well as dramatically speed up business processes. So where is the problem?
AI communication problems
The first communication problem arises between participants of the solution implementation process. Unfortunately, product developers and customers speak different languages and often focus on different features of the proposed solution. Due to such misaligned visions of AI and its potential, the technology capabilities are underutilized.
The second communication problem arises when a customer interacts with the final product and perceives it as something hostile or suspicious due to a lack of information about its benefits and functions. Let’s consider recruiting robots. HR people are more concerned about their jobs and afraid of robotic automation possibly causing lockouts rather than interested in studying the solution capabilities.
How does the AI Responsible approach solve them?
It is simple. This approach assumes transparent unified communication with many target groups, and can be used by both AI-powered product developers and employees who are responsible for implementing artificial intelligence solutions in their companies.
AI-based decisions need to be explainable in order to be trusted. According to a recent PwC survey, 84% of CEOs agree with this statement. As well as buyers. Consumers want the convenience of services tailored to their needs, together with the peace of mind knowing that companies are not unknowingly biased against them — and that their government will protect them with laws regulating how their data can be used. As we can see, being just useful is not enough. It’s important to get clear, and we at NNTC go this way with each of our products.
The “AI Responsible” formula has five key components to identify AI responsibility:
- GOVERNANCE will introduce clarity to AI objectives and tasks within an organization. Before developing or implementing a solution, assign and document the responsibility of each process participant. Then, align AI with the current business strategy and identify processes that need to be optimized using AI. What result should we expect? How will it manifest? Who will monitor the effectiveness and document problem areas? Can you give guarantees that the solution will be effective?
- ETHICS AND REGULATION. AI-powered solutions must be developed in accordance with the established legislation and regulations of the organization, which should be morally responsible and ethically defensible. Notifying of compliance with the established guidelines will build confidence in AI.
- INTERPRETABILITY AND EXPLAINABILITY. Let the user understand why a particular AI reached a particular decision. Explanations should be tailored to the different stakeholders, including regulators, data scientists, business sponsors, and end consumers: never leave them uninformed making your product into a mysterious black box for them.
- ROBUSTNESS AND SECURITY. Eliminate all possible risks and flaws in your product, and timely release necessary updates and patches. Tell your customers what problems have been solved, quickly fix bugs, and listen to feedback.
- BIAS AND FAIRNESS. Fight against discrimination and train your AI to perform its functions fairly and equitably.
Only those who are responsible will survive
The ability to develop AI responsibility is a cornerstone of its further development and recognition. In a world filled with a variety of solutions from styling photos like watercolor paintings to recognizing car license plates, the advantage will belong to a reasonable developer who explains algorithms and is ready for a dialog with users.
