Responsible, Ethical AI?

Thought provoking.  Responsibility should be linked back to the business outcomes that emerge.  But you could argue that AI and analytics methods allow these to emerge more readily and in stronger context,  so perhaps that aspect does need to be 'responsible'.   So if I am now able to instantaneously recognize someone via AI methods,  what ethical issues does that create?     Still being considered.  Responsibility delegated or otherwise

Want Responsible AI? Think Business Outcomes  In K@W:

Mala Anand, author of this opinion piece, is president of intelligent enterprise solutions and industries at SAP.

The rising concern about how AI systems can embody ethical judgments and moral values are prompting the right questions. Too often, however, the answer seems to be to blame the technology or the technologists.

Delegating responsibility is not the answer.
Creating ethical and effective AI applications requires engagement from the entire C-suite. Getting it right is both a critical business question and a values’ statement that requires CEO leadership.

The ethical concerns AI raises vary from industry to industry. The dilemmas associated with self-driving cars, for instance, are nothing like the question of bias in facial recognition or the privacy concerns associated with emerging marketing applications. Still, they share a problem: Even the most thoughtfully designed algorithm makes decisions based on inputs that reflect the world view of its makers.

AI and its sister technologies, machine learning and RPA (robotic process automation), are here to stay. Between 2017 and 2018, research from McKinsey & Company found the percentage of companies embedding at least one AI capability in their business processes more than doubled. In a different study, McKinsey estimates the value of deploying AI and analytics across industries to be between $9.5 trillion to $15.4 trillion a year. In our own work we have seen leaders in industry after industry embrace the technology to both find new efficiencies in their current businesses and to test opportunities with new business models.

There is no turning back. .... "