PROMOTING TALENTS IN THE AI-ERA

PROF DAVID DE CREMER

KPMG CHAIR, UNIVERSITY OF CAMBRIDGE

PROMOTION IN THE AI-ERA: HUAWEI AND PROMOTION OF THE YOUNG

Energy makes for vital organizations

Agility and pro-active strategic thinking requires energy and a strong drive to succeed. Stays hungry in achieving

innovations/success

Contribute in your prime

Encourage young employees to maximize their contribution to the company while being in their prime. Innovation requires high-

energy searches combined with a certain sense of risk-taking are undertaken.

Give room to talent

Lower the management costs in its innovation strategies identifying and training new managers in great numbers.

Fast-track promotions create new role-models

Ren Zhengfei notes, “some of our young employees are working conscientiously, and growing very quickly.”

WORKING IN THE AGE OF THE ALGORITHM

• Survey Accenture (2017):

85% of executives want to invest more extensively in AI-related technologies over the next 3 years.

Application of simple linear algorithms have been shown to outperform human judgment (e.g. medical

diagnoses and employee performance).

Current debate: which jobs enacted by humans will be replaced by AI.

GARY KASPAROV AND AI

• Russian chess grandmaster and former world

champion

• In 1997 the first world champion to lose a

match to a computer under standard time

controls, against IBM supercomputer Deep

Blue

EXAMPLE OF AUTONOMOUS AI AND MEDICAL PROFESSIONALS

• About 86% of healthcare provider organizations, life science companies, and technology vendors to healthcare

are using artificial intelligence technology.

• Machine learning algorithms data from hundreds of thousands of patients. Could predict with more than 90%

accuracy the chance of a patient dying after 24 hours of their hospitalization.

• By 2020, these organizations will spend an average of $54 million on AI projects.

AUTONOMOUS AI AS THE ONLY WAY FORWARD?

• Although the advantages of automation are unquestionable, automation may not be universally desirable

• People sometimes do not want to take advice from algorithms and are less willing to consider this advice than if

it was offered by another person

• “algorithm aversion”

• People do not like complying with a black-box

DESCARTES

• Replication of the body: Industrial revolution

• Replication of the mind: AI

• The birth of “autonomous” AI

• Consciousness is needed! (cf. meta-thinking)

WHAT SKILLS DO FUTURE EMPLOYEES NEED

• Theory of the ‘unknown unknowns’.

We know what we know, sometimes we know what we do not know, but increasingly there are more things of

which we do not realize that we do not know.

Increase in uncertainty

Train people to deal with uncertainty and foster creativity

• Use people’s strengths: emotions and societal focus

• Think about consequences for society

• How to manage and lead AI?

• Ethics and AI – recognize the broader societal context

MBA’S AS THE NEW NORMAL

• Management By Algorithm (MBA)

• The World Economic Forum’s Global Agenda Council

conducted a survey on the Future of Software and Society showing

that people expect artificial intelligence machines to be part of a

company’s board of directors by 2026.

• Our research shows that this kind of reasoning is too limited and

may even pose a threat to the legitimacy of AI in work settings.

TECH INDUSTRY AND NOT CONSIDERING CONSEQUENCES

• Innovation only bias

OUR CHALLENGE

• Responsible and anticipating leadership as an obstacle for tech innovation?

• “Change is good, but change with a purpose is even better”

• Automation is desirable when people seek to maximize convenience but that it is not inherently valuable when feeling loss of

control in decisions that are moral in nature.

• When automation replaces human skill or effort, it eliminates feelings of decision-control, increases feelings of exclusion and

introduces fear about morality.

WHAT YOU NEED TO REALIZE

• Many business decisions involve moral judgment

dimensions

Conflicts of interest – time dimension

• Philosophical questions regarding ethics need to be

solved before AI – which input algorithm?

Pragmatism

Principle

Legal

WHAT YOU NEED TO REALIZE

• Our assumption:

• Idea is not to zoom in on the strategy that AI replaces humans, but rather on collaboration and co-creation

• Consequence:

• Address question of how algorithms can be included in the chain and group of humans and not vice versa

(broad intelligence, embeddedness in society and values)

WHAT LEADERS HAVE TO DO IN THE AI ERA?

• Human leadership needed for:

Facilitating the use of AI – making its use more

effective (legitimacy)

Moral, societal and values sensitivity

Managing the new diversity

• Training required in philosophy, psychology and

managing organizations

THANK YOU

d.decremer@jbs.cam.ac.uk

www.daviddecremer.com