Artificial Intelligence is the science of machines which are able to adjust their behavior to changing circumstances.

Ray Dalio, founder and head of Bridgewater Associates, pioneers implementing AI to support and replace human decision making. Talking about his ambitious plan to let AI decide on 3/4 of all decisions in the next five years, he states: "A lot of management is basically information work, the sort of thing that software can get very good at". 

Experimenting With Management. 

Artificial Intelligence Starts To Change The Way We Work.

Author: Matthias Maucher

Imagine a world in which each time you ask someone a question, that person will give you the same answer as every other person would, since he has the same basic information to process the issue. Such a rational world would be based on algorithms. Artificial Intelligence describes a system that is able to adapt its reasoning and conclusions to changing circumstances even though the input factors are the same. You may have encountered AI in the streets already. Self-driving cars are well known examples for AI usage. IBM's WATSON is another example, and is famous for being the first AI system which won against two Jeopardy! game champions in 2011. Compared to that machine driven rationality, human judgement and decision making rather appears like throwing darts with closed eyes. Research revealed that if you ask two project leaders about the time needed to complete a task with given resources, their answers will differ. The same can be true if you ask one of the two a second time, a few days later. The hours predicted differ by 71%, on average. Professionals tend to assess situations differently even though the relevant input information is the same. This less consistent judgment can have a significant financial impact if the decision is about risk assessment or pricing. Not surprisingly, investment banks start to invest in AI. Don Duet, cohead of Goldman Sachs technology division, said "you know, we see that the ability to take data and help turn it into information as an asset as a core part of our strategy". "It's a very important technological as well as business strategy for the firm and is helping us move to a better degree of data-driven businesses as well as really deriving expertise, content, and knowledge of information."

The next level of AI usage is its' application in business management. Ray Dalio, pioneering this evolution, aims at overcoming human limitations using AI for decision making. The journey toward future thinking has begun!  

Biases and noise limit the accuracy of human decision making

Professional judgement and decision making, as we know, is influenced by human biases such as the anchor effect. Anchoring describes the common human tendency to rely too heavily on the first piece of information offered (the "anchor") when making decisions. Apart from biases, human decision making is influenced by what we call noise. Noise is driven by emotions and moods, among others. It's prevalence has been demonstrated in several studies. A typical trait of a noisy result is its variability. An example from the kitchen: If your morning egg is always overcooked, your cooker is biased. If each morning you find a different outcome on your spoon, from slimy to boiled, than your cooker is noisy. Except from breakfast, you might have encountered noise in business, in situations when the so-called expert judgment was required, like pricing, valuation of real estate, risk assessment, strategic decisions, financial statement analysis and others. Our case of the two project managers above is also an example of this. 

An AI-like management philosophy 

At the moment, we are not aware of an AI-like management philosophy. If there was one which was close to this, it might be the management philosophy of Ray Dalio. Constant improvement, detailed truth, absolute openness and radical transparency stand at the beginning of more than 200 management principles covering all relevant management topics. It would go beyond the scope of this article to go into more detail on all of them here. However, we will address Ray Dalio's insights in further notes. To give you a first idea, the excerpt below is a copy of his reasoning:

"Every organization works like a machine to achieve its goals. This machine produces outcomes. By comparing the outcomes to the goals, those running the machine can see how well the machine is working. ...

The machine consists of two big parts - the culture and the people. If the outcomes are inconsistent with the goals, something must be wrong with the machine, which means that something must be wrong with the culture and/or the people. By diagnosing what is wrong, designing improvements and implementing those improvements, the machine will evolve."

Translating management to AI

Bridgewater Associates' use of AI translates Ray Dalio's management philosophy into machine learning. The case in practice: AI constantly gathers a variety of information about employees and tasks to be done. Input data includes such elements as peer reviews, employee testing and open tasks, among others. Based on that information and depending on changing external factors which the system analyzes as well, the system assigns specific tasks to employees and provides instructions on how to action them. Human employees follow those instructions. The system closely observes the individual approach and evaluates the information gathered for automated feedback loops and performance assessments. This allows the system to guide on hiring, terminations and promotions too.

Thoughts from a talent management and leadership perspective

As far as we are aware, Ray Dalio is a first-mover in using AI for internal management. As the journey has just started and as publicly available information is still limited, we are curious to see how this experiment evolves. What does it mean for human employees if their work is guided by AI? What is its impact on the fulfilment of basic human needs such as work which is meaningful, the desire for an autonomous approach and the wish to have an influence on the results achieved?

An AI-guided working environment can improve human team's interaction, if certain prerequisites are fulfilled. One of the most important ones' certainly is that the system allows people to develop a perception of making an impact and learning. Yet, if AI is perceived as a micro manager who focuses on task and monitoring, people's interaction will suffer quickly. Intrinsic motivation will thus replaced by monetary incentives, for instance, which creates a highly competitive environment without positively impacting the overall performance. To avoid such developments, the quality of human interaction and, what we call people oriented leadership, is even more important in an AI-guided environment.


The way AI and human employees interact will require a detailed analysis to assure value added and a healthy corporate culture.

The AI journey has just begun!


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