Category: behavioral

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Too much electricity

  • The “All electric society” has a problem very few other societies have. It has to make provisions for cases when there is too much electricity in the network. What seems like a problem some energy poor countries, regions or people will dream of, has become a costly matter in California beyond Californication. A report in “The New Yorker”  2025-7-9 by Bill McKibben highlights the fact that California had to pay neighboring states to take and consume its surplus production of electricity. With a surplus production of 1.5 the total demand of electricity the costs become a sensitive issue. Intelligent distribution and appliances can absorb huge additional quantities, but the network stability has to rely on a suitable infrastructure for this as well. Optimizing de-central production and consumption is the easy theoretical solution. Hence, the all electric society has to deal with affluent power generation in the near future more than with too little electric power. Prepare tp run your AI-systems in a decentralized manner to safe the planet from more nuclear power plants and nuclear waste as a corollary. Electric power has always been an issue of political power. The all electric society will not be different in this respect. A decentralized prosumer society, therefore, is an empowerment of citizens, comparable historically maybe only with the French revolution or the technological progress spurred by the discovery of Ohm’s law.

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All electric now

The shift over to the “All electric society” is easiest in sunny states like California in the USA, Africa or Southern Europe. For other regions of the globe not only the production of energy through the sun is a bit less abundant, but the storage of the sun’s energy production for deferred use is the next challenge. Countries of the globe near the equator have to balance 12 hours daylight with 12 hours night, countries far from the equator have to balance additionally more long-term between short winter days and long summer light.
Different energy storage solutions have to be envisaged.
On a daily basis or even weekly basis, battery energy storage systems (BESS) can do the trick. These systems become more costly for high capacity, longer duration storage. Battery size and price quickly become an issue. The number of electric vehicles (EVs) that have this more intelligent BESS is rising. This makes it possible to eventually use this storage capacity, if your car is sitting around your home or office for most of the time anyway. To make the “all electric society” function 24 hours, energy storage has to be planned at the same time as production and consumption patterns. The all electric prosumer will be the de-central “pro-store-sumer” in the 21st century.

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Work and Time

The link between work and time has been evolving as a major element of social progress over centuries. In what younger generations seem to take for granted, <40 hours week, paid time off-work. 4-5 days per week to name only the major ones, has been the result of huge struggles and hustles driven by employees and their trade unions to achieve such milestones. The current debate to get employees back into offices and/or to work longer hours again, is also in the end a debate about work and time. The advantage of working from home consists among other factors in saving a lot of valuable time and stress from commute to work. This unaccounted time to go to work has become a major health hazard even in an apparently comfortable company subsidized car or any other means of transportation. The traffic jams of so-called rush hours, when in fact everybody is slowed down, are a serious health hazard usually ignored by employers. However, these hours are a major part of the work-life-time balance of employees. In many negotiations and collective bargaining about working time this is the big elephant in the room rarely addressed.

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Green trade flows

The statistics on trade flows reported by the UN Department of Economic and Social Affairs have a comprehensive data base in the background. The descriptive inspection of the raw data on trade flows comprising solar panels, batteries and electric vehicles shows a stark imbalance of how future-proof the trade between countries is. The New York Times (David Gelles et al. 2025-6-30) has put this information into an impressive graphical design to show the magnitude of the imbalance of how China trades in green products with the world and how the USA is losing out on future-proof low carbon emission trade. Despite the fact that China is still heavily emitting CO2 today due to burning coal for electrical power, the investments at home and trade with the world is moving into the opposite direction. We have seen many of these industries at risk in Europe, like solar panel production, batteries and increasingly electric vehicles, without the western countries getting organized to address crucial business and economic challenges. Falling behind in these industries and trade will shift global balances in the near future. Renovation through innovation is more promising than holding on for another decade to inefficient and more polluting energy sources. Repairs of homes and buildings have long lasting effects, which we can, nevertheless, change today.

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Ultimate Step

Reports in the New York Times, The Guardian and Le Monde in recent weeks have brought to our attention that there are shocking ultimate steps undertaken by several employees of public services. In the case of the British post office a decade long inquiry has uncovered that 13 suicides of employees occurred after they had falsely been accused of fraud. A long time ago in France Telecom a series of suicides was also attributed to a harsh personnel policy. The Office of Public Finances (DGFiP) is confronted with a series of suicides in 20025 of 12 employees who apparently made the ultimate step to put an end to their life. Not all is to be blamed on the enterprises or public services concerned, however, they failed or omitted attempts to prevent the ultimate steps. Initiatives like peer listeners as anonymous contact points or access to psychological counseling are necessary parts of a responsible human resource practice, even if it might not be a sufficient condition to avoid the ultimate step in some instances. In many cases employees go far beyond their mental capacities in terms of commitment to their work, they should not be left alone in case of severe consequences.
Burn-out, for example, needs to be tackled as part of the responsibility of enterprises and public services alike. It is highly unfair to put the costs of psychological consequences on the shoulders of families and the state. Investigations into toxic leadership styles and the current revival of “workaholic” work ethos will have serious negative consequences for families and society as whole again.

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Bench the benchmarks

In the social sciences as well as in engineering it is common practice to use benchmarks as indicators of performance. Thereby, several countries or regions within a country are compared with respect to quantitative indicator. Let’s take employment ratios. A higher employment ratio, which includes many persons working few hours in part-time work, is different from a slightly lower employment ratio, but hardly any part-time employees.
The same rationale holds true for benchmarks of AI systems or the newer versions of agentic AI that are under construction in many fields. The paper by Yuxuan Zhu et al. (2025) proposes the ABC (agentic behavior checklist) for agentic AI developers. The reporting of benchmarks by such models should include (1) transparency and validity, (2) Mitigation efforts of limitations and (3) result interpretation using statistical significance measures and interpretation guidelines.
The aim of this research is to establish a good practice in establishing benchmarks in the field of agentic AI. The sets of criteria to test for is large and the focus of how the agentic AI treats, for example, statistical outliers much above or below the average i.e. (> 2 standard deviations from the average) assuming a normal distribution, is one case of application only.
We welcome the efforts to bench the benchmarks in the field of AI as is common practice in other sciences as well.

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Learning by using

Is learning by using different from learning by doing? In an economic model to test the employment/unemployment impact of AI in the USA, Wang & Wong (2025) suggest an important impact of employees’ productivity due to learning by using AI. In terms of the traditional language of economics the employees who use AI in their work shall have comparative advantage to those who don’t.
In a model of job search in the economy there is the additional possibility, similarly to robots previously, that certain tasks maybe influenced by the, more or less, plausible threat of an employer to replace the employee by training an AI system to perform the tasks. The credibility and acceptability of such threats are likely to impact wage claims and unemployment risks. All these effects do not happen instantaneously, but evolve over time with varying speed. Hence, calculations of effects have high error margins. The resulting model yields oscillations of “labor productivity, wages and unemployment with multiple steady states in the long run”.
Learning by using seems to be a good description of what occurs at the micro level (the employee) and at the macro level of an economic sector or the economy as a whole. Society may guide the use cases of AI just as much as the business case to use AI, for example in the creative industries as infringements of copyrights may occur on a massive scale. However, learning by using is not free of risks to society at large. Just like allowing people to use automotive vehicles has lead and still leads to thousands of deaths annually, learning by using produces external costs. Overall, this is another case for a benefit/cost analysis for businesses, the economy and society.

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Pepper and Nao

We have seen many persons that became somehow emotionally touched when addressed by Pepper or Nao. These 2 versions of a humanoid robot have served for thousands of persons as the first welcoming moving information desk. I have been guided through museums (DTM, Berlin) and exhibitions by this robot guide with a friendly outlook. Beyond those experiences there is a lesson in industrial policy to be learned from this innovative French humanoid robot. The start-up enterprise was founded as early as 2005. With a substantial funding of ½ billion € from Softbank the enterprise could develop robots for the fields of personal companionship, education, restaurant services or personal care for the elderly.
We have seen the robots at international fairs in several countries, but the prohibitive costs have limited the rapid spread of the robots to broader applications. Subsequently, the decline of the enterprise, or not reaching financial targets fast enough, caused the loss of financial support for the enterprise. In 2025, Aldebaran filed for bankruptcy and the patents will be sold to the best offers. The employees received generous packages of departure and will most likely find rapidly jobs in other robotics, IT or AI related fields.
The loss is probably greatest for the persons who were serviced by Pepper or Nao in elderly homes or the Swiss hospitals, as spare parts or updates will no longer be available. The humanoid robot story is yet another case where the social, economic and financial context of technology is overriding the technological innovation process.

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AI 2nd round effects

The most popular topic currently is AI.
Most writers, assisted by some form of AI, will deal with the 1st round effects of AI. These consist in the immediate consequence of the use of AI in office work, medical and military applications, music and all producing or creative industries. As an economist you take the input – output matrix of the economy (OECD countries) and take AI as an additional dimension of this I/O matrix, for example. The result is an AI-augmented model of the economy. This 3-dimensional cubic view of the economy asks to reflect on the potential short-term and medium-term impact of AI.
Let’s take the example of translation and editing services. AI will in the short-term or the 1st round effects make it easier to offer mechanical translations with fast turnaround. Most likely, this will lead to less translators needed for routine translations of longer texts, which would otherwise be a very costly endeavour. The 2nd round effects, however, will make the expert knowledge of translators of texts, where every word counts, more necessary in order to provide the best version of a translation targeted on specific audiences.
In the legal domain, for example, the precision of words is primordial and errors can be very costly. Hence, the 2nd round effects of AI in this field will increase the demand for high quality translation services more than before the use of AI. The important shift consists in these 2nd round effects of AI, which give a push to multilingual societies as just one medium-term outcome.
Please use AI to read (listen) to this paragraph in your native language or even dialect using your favourite AI-tool.

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Pet effects

Pets have effects, some might cancel out each other. In psychology there is a long debate about the pet effect, which claims that pets have overall a positive effect on a person’s well being. This claim has recently been debunked. Many persons have taken over the care of an animal for their own comfort and regular daily routines. The Covid crisis had spurred such behavior in many people, but the scientific evidence taking into account the responsibilities that come with ownership of a pet, can outweigh the benefits of having company. The choice of a pet should certainly not be an easy or haphazard one. There is a need to consider the full range of pleasure and responsibilities. Traveling with pets and vacation times pose additional challenges that can cause stress to owners as well. Dog sitting or pet sitting platforms have been thriving since the Covid pandemic and this is to the benefit of everyone involved.