How Digital Ethics Enables Trust In Business AI

Guido Wagner

Artificial intelligence (AI) technologies open doors to new possibilities that can enrich (and potentially harm) the lives of many people. Digital ethics can help manage the risks expected from related changes in the labor market and our society.

Growing automation may create a world where people have to work only a few hours a week – although it will be a challenge for humanity to get there without social unrest. Support for this trend comes from the tendency to realize intelligent enterprises by using embedded AI systems in production and business management. Personal assistants will be the spearhead of a new generation of user interfaces.

Intelligent systems will be able to communicate with users in the style of human communication. Where Mr. Spock in the Star Trek Universe needed to press buttons to interact with machines, there will be voice & gesture recognition and perhaps thought-controlled interfaces. Using augmented reality glasses, for instance, everything can become a device – because any wall or table can be augmented with controls useful to interact with AI.

Sounds like a bright future for the coexistence of humans and machines. We just need to ensure it’s done intelligently – ensuring that IT primarily serves humans. As with any advanced technology, the impact of AI on individuals and human society is difficult to assess. Because AI is relatively new and the benefits aren’t yet obvious, people fear they will lose their jobs for efficiency reasons or because they think AI is taking over. This results in a lack of trust in AI.

For a successful integration and broad acceptance of AI technologies in our daily business, the user’s trust is therefore crucial. The challenge is that trust is not built just on the exchange of computational results – it happens on a personal level. For example, if a personal assistant is quite helpful but unveils private data or has an unpleasant voice, humans will not place their trust in it.

We need to show that trust and automation efficiency can be partners, helping each other to grow. A valid starting point would be a set of design principles to use in the architecture of systems for the intelligent enterprise. Here is a proposal developed and used by SAP Design:

  1. Intelligent automation: When driving the automation of a process, it should be done with caution and foresight.
  1. Human augmentation: Technology should be used to augment and improve human capabilities rather than patronize people.
  1. Keep humans in the loop: Users will rely on honest, transparent processes and reasonable methods to come to their own conclusions.
  1. Digital ethics: We must seek out AI partners who subscribe to human ethical values and social behavior. Two important elements will be managing bias and potential misuse.

In fact, the last principle has the power to connect trust and efficiency. If an AI behaves along broadly accepted ethical lines, humans can be sure to be treated fairly and individually, even in times of automation.

Trust and efficiency as partners

Trust can also be built by using a communication style similar to that used by humans, finally fulfilling the requirements of the Turing test. AI would need to consider cultural and social conventions beyond ethical rules. Such conventions may depend on the age of the user and his or her social environment. Of course, trust requires that AI complies with legislation – especially data-privacy regulations. These topics are important but will not be looked at in depth here.

Before we can start to implement or build AI systems, we need to think about the potential impact. We need to define goals, requirements, and operational boundaries from a human perspective. Start with an inventory of the system’s tasks and boundary conditions. Being aware of related questions helps to determine areas where ethical challenges are waiting.

Asking questions like the following is helpful for understanding what will the AI do and estimating its impact.

  • Which of the AI system’s tasks might affect human life?
  • Will machines be better than humans at this task? In which areas?
  • Will humans benefit from the handover to AI? Which user roles will benefit?
  • What advice will be given and which decisions made by the system?
  • Which specific types of information will the system be allowed to handle (inbound, outbound)?
  • Which type of information will the system need to learn?
  • Could there be situations which require specific ethical behavior (e.g. emergencies)?
  • Which technologies will be used (e.g., UX, machine learning, etc.)?
  • What physical entities may be accessed or affected (e.g., production machines, robots, traffic lights)?
  • Will environmental sustainability be improved by using AI?

Knowing what AI should do and how it is supposed to improve human life, we can start thinking about potential ethical challenges. A checklist of questions is helpful to consider aspects of ethical systemic behavior in specific situations. A proposal for a set of questions will be covered in the second part of this blog.

To learn more about digital ethics, read “Checklist Of Ethical Design Challenges For Business AI.”

Guido Wagner

About Guido Wagner

Guido Wagner is responsible for invention projects in SAP Design. He focuses on user experience optimization in a digitalized business environment. Preparing for the future of work through sustainable artificial intelligence that improves the way people live is his passion. Share your thoughts with Guido on LinkedIn.