How we can change our lives

Six theses on how AI prognoses will change our lives

"Artificial intelligence" is almost the definition of a hype, "wrote the market research company Gartner just under a year ago and added in the same way last February: The potential is enormous, but implementation took longer than expected. With AI, too, big words lead to big expectations and big misunderstandings - at the moment everything that has to do with computer science seems to be AI in some way.

It is far simpler to ask the question of how artificial intelligence works. Put simply, it enables better predictions. The search results on Google? Predictions about my interests. Recommendations on Amazon? As well. Siri's speech recognition? Dito. So what AI does are forecasts. This also applies to much more complex areas such as the logistics of a retailer, traffic flows or the development of a tumor.

These few examples make it clear: The possibility of radically more precise forecasts will change our lives just as radically. This gives rise to a multitude of new questions: How will decision-making behavior in business and in private life change if we can better predict the future? What is technically possible? And what are the most important economic and social consequences? - An introduction in six points:

1. The future belongs to math magicians

For a long time, forecasting was a frontier science, and predictions were often more magic than science. Now a change is taking place: more science, less fiction. Because in the course of digitization, predictions are getting better and better. They are mainly based on the growing availability of data, the performance of computers and on machine learning - a branch of artificial intelligence. Algorithms are trained to recognize empirical relationships in large amounts of data. For example, they learn to distinguish moles that are potentially carcinogenic from harmless freckles and achieve an accuracy that exceeds that of human experts. In addition to medicine, such algorithms are increasingly being used in other sectors such as legal and taxation, marketing, transport and agriculture. An essential difference between mathematical and magical methods is that the forecasts can be checked and compared in real time with real developments and competing forecasts - which in turn improves the forecast quality.

2. The present becomes more readable

Algorithms do not confer clairvoyance. They do not let you see into the future, but they make facts and relationships visible. Predictive analytics are task-specific prediction systems that do not aim at the big picture, but at the known unknowns. The focus is on short-term or real-time forecasts, for example for weather, traffic conditions or epidemics. Known risks become more predictable and new risk factors can be discovered earlier. With better predictive technology, the radius in which we can move safely increases.

3. Experts on Demand for everyone

First of all, the new forecasting technology automates the work of experts. Forecasting systems will be used from financial and travel advice to nutrition and couples counseling. This makes professional advice cheaper and available to the mass market. Smart assistants will create individually evidence-based predictions and provide recommendations on the right training, diet or preventive programs. This means that even people who could not afford personal advice can consult virtual top experts at any time - in case of doubt, several at the same time. In addition, experts also find qualified support.

4. New forecasting tools take the strain off your head

Forecast tools will also become more and more popular in everyday life if they make life easier. Is the shopping list complete? The doctor's appointment made? Washed the laundry? And when do the children have to be picked up tomorrow? Such organizational questions, which clog the brain as it were, are called "mental load". “Smart assistants” such as Alexa or Siri could one day take over this mental load of household and family management - just as washing machines, vacuum cleaner robots and ready-made meals once helped to reduce the amount of work involved in housework.
Nobel laureate Daniel Kahnemann differentiates between two types of thinking: the fast, instinctive and emotional "system 1" and the slower and more rational "system 2". The fast, emotional thinking of "System 1" takes place automatically. However, it tends to make incorrect assessments and make hasty decisions. The logical formation of judgment in “System 2”, on the other hand, has to be activated consciously and is quickly utilized. Smart assistants could therefore take over its function: Whenever things have to be thought through, different factors compared and alternatives checked, the thinking could be delegated to the prediction machines. Because especially in environments with a lot of data (fraud detection, medical diagnoses), machines are superior to humans. Soon it would be inconceivable to make important decisions without reinforcing machines. Perhaps it would even be considered irresponsible to choose a partner, employee or politician without an algorithmic expert opinion.
Of course, there would be a risk of increasing infantilization of society: Why still learn when an expert mind in your pocket knows everything better and solves all problems? On the other hand, exertion can be pleasurable in thinking, as in exercise, and fitness for the brain could soon become just as normal as it is for the body.

5. Forecasting cannot be a privilege

The spread of the forecast systems can hardly be stopped. If the competition can predict who will need new glasses and when, how many sausages a certain supermarket will sell the Saturday after next and which new employee will do the most, then those who only rely on their gut instinct can quickly go out of business. Decisive for the social acceptance of the forecasting technology will therefore be who will become smarter with its help: all people or only a very few? - Prediction machines are thinking tools that help us navigate a hyper-complex world. In the sense that our knowledge of ourselves and the world grows, that's a good thing. The danger does not arise from this excess of knowledge, the danger arises from the unequal distribution of knowledge. In order to limit the misuse of forecasting technology, one must democratize its use.

6. Forecasting improves decisions

So far, important decisions have mostly been reflected in retrospect: What would we change if we could start all over again? Better measuring instruments expand our imagination by visualizing spaces of possibility and thus offer a laboratory in which we can simulate different development paths. So if we had better tools, we could ask questions in advance and decide differently if we don't like the prognoses: for another partner, another job, another apartment. Or we could avoid situations and people that we would rather never meet. A decisive feature of a good forecasting system is that it expands the scope and shows alternative development paths - and not that it is dictated by fate. Because those who know more about themselves have more opportunities to change their future. Forecasting tools help to gain new insights about yourself based on better data and thus to better understand who you are, what motivates you, what makes you stressed and what makes you happy. Only those who know themselves can reduce their dependencies and expand their scope for decision-making. "Know yourself" is the inscription at the entrance to the Oracle of Delphi.