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Der zweite Blick – A Second Look
In Germany, there is an ongoing debate about whether people are working too little. The discussion revolves around part-time employment, sick leave, and work-life balance.
At the same time, politicians and business leaders are embracing automation and artificial intelligence, hoping to achieve more with less human labor.
Both positions may have merit.
But taken together, they raise a question that is surprisingly rarely asked in the current debate:
How much human work will we actually want—and need—in the future?
What the Criticism Gets Right
The average number of hours worked by employees in Germany is relatively low compared with other European countries.
That does not mean, however, that full-time employees are working particularly short weeks.
According to Germany’s Federal Statistical Office, full-time employees normally worked an average of 39.9 hours per week in 2025.
The lower overall average is largely explained by Germany’s high proportion of part-time workers.
What Are We Actually Measuring?
The number of hours worked is not, in itself, a measure of an economy’s success. It is one of the resources used to produce economic output.
What matters is what those hours produce.
An economy can increase its output because more people work longer hours. But it can also produce more because the same number of people, using better technology, more efficient organization, and greater knowledge, accomplish more in the same amount of time.
That is why productivity per hour worked is at least as important as the total number of hours worked when assessing an economy’s performance.
Gross Domestic Product, or GDP, is often used for this purpose. It measures the value of goods and services produced within a country.
Gross National Income, or GNI, takes a somewhat different perspective. It focuses on the income received by people and businesses resident in the country.
Both indicators tell us a great deal about economic performance.
But neither tells us everything about whether people are actually enjoying a better standard of living.
Consider a simple example.
Suppose technological progress made it possible for a society to produce the same economic output in 30 working hours instead of 40.
GDP would not automatically increase.
Yet the ten hours of additional free time would represent a genuine improvement in people’s lives.
That improvement would barely appear in GDP.
Leisure time, unpaid care work, health, and quality of life are all aspects of prosperity that conventional economic indicators capture only imperfectly.
This distinction matters in the current debate about working hours.
The number of hours worked tells us relatively little about how productive an economy actually is.
At least as important is how much value is created during each hour.
If automation and artificial intelligence increase that productivity, economic progress may consist precisely in achieving the same results—or even better ones—with less human labor.
When Machines Take Over Human Work
This is where automation and artificial intelligence change the perspective.
Their economic purpose is precisely to perform tasks faster, more cheaply, or with less human effort.
Activities that previously required substantial amounts of human working time can increasingly be performed by machines.
That is not necessarily a loss of economic capacity.
On the contrary, it can represent a gain in productivity.
What strikes me about artificial intelligence is how often the very technological progress from which we expect productivity gains is simultaneously described as a threat.
Consider AI-generated music.
Artificial intelligence can perform certain stages of music production faster and at lower cost. At the same time, it can open up new creative possibilities for people.
That does not necessarily mean that the human element disappears.
Perhaps what changes is which human qualities become scarce—and therefore particularly valuable.
Personality. Experience. Judgment. The direct encounter between people.
Throughout history, technological progress has repeatedly replaced certain forms of human labor while creating new activities and occupations.
The crucial question, therefore, is not how to preserve every existing task.
It is whether a society can put the human labor that is no longer needed in one area to meaningful use elsewhere.
And whether the resulting gains in productivity actually lead to greater prosperity.
Who Benefits from Higher Productivity?
If machines and artificial intelligence perform an increasing share of the work that creates economic value, we face more than the question of how much human labor will still be needed.
We must also ask who will benefit from the resulting productivity gains.
As long as paid employment remains the principal means through which people earn an income and obtain social protection, the declining importance of human labor could create a fundamental tension.
An economy may become increasingly productive without the additional prosperity automatically reaching everyone.
This brings us back to a familiar question about the distribution of wealth—but in a new form.
If an increasing share of economic value is generated not directly by human labor, but by capital, software, data, and automated systems, we need to reconsider the role paid employment will play in providing income, social security, and participation in society.
This does not necessarily mean that everyone must become more equal.
The more immediate question is what rules should govern the distribution of the benefits of a more productive economy.
Here, I find a thought from the political philosopher John Rawls particularly useful.
In A Theory of Justice, Rawls does not simply ask whether everyone should possess the same amount of wealth.
Instead, he asks what principles would make the basic structure of society fair.
According to his difference principle, social and economic inequalities can be justified if, under fair conditions, they also benefit those who are least advantaged.
Applied to our question, this suggests something important.
If automation and artificial intelligence generate enormous increases in productivity, it is not enough merely to ask whether those gains are being achieved.
We must also ask whether the rules governing their distribution can reasonably be regarded as fair.
Work Is Not an End in Itself
If a task can be performed just as well—or better—with fewer hours of human labor, that is not inherently a loss for society.
Quite the opposite.
Making work easier and reducing the human effort required to accomplish something has always been one of the central purposes of technological progress.
It would be questionable to hold back new technologies primarily to preserve activities that could be performed with less human effort.
That does not mean, however, that we can ignore the consequences for the people affected.
Technological change can diminish the value of established occupations, make existing skills obsolete, and create painful transitions.
A society’s responsibility is therefore not to preserve every existing occupation indefinitely.
It is to provide people with security, opportunities to acquire new skills, and a fair chance to participate in the benefits of technological progress.
Only then can an increase in business efficiency become a gain for society as a whole.
So, Are We Really Working Too Little?
The answer is less straightforward than the current debate often suggests.
An aging society cannot simply afford to dispense with human labor.
High rates of part-time employment, substantial numbers of absences due to illness, and a shrinking labor supply are real challenges.
But it does not necessarily follow that maximizing the number of hours worked should be our objective.
The more important question is not merely how many hours people work.
It is what they accomplish during those hours.
If productivity increases through technology, better organization, and greater knowledge, a society may be able to generate the same—or even greater—prosperity with fewer hours of human labor.
In that case, shorter working hours would not necessarily reflect a declining willingness to work.
They might instead be evidence of a higher level of technological and economic development.
Perhaps part of the problem lies in the very statement that people are „working too little.“
It assumes that more work is, in itself, a sign of strength.
But in an economy increasingly shaped by knowledge, automation, and artificial intelligence, progress may lie precisely in reducing the amount of human labor required.
The challenge would then be to turn those productivity gains into prosperity, security, and greater freedom over how we spend our time.
Perhaps we should therefore spend less time arguing about whether people work „too little.“
Instead, we should ask how much human labor we will actually need to sustain our prosperity in the future.
And if technology can relieve us of some of that work, the question is not only how we distribute the resulting economic gains.
It is also what we intend to do with the time we have gained.
Sources and Notes
Federal Statistical Office of Germany (Destatis): „Vollzeitbeschäftigte arbeiteten 2025 im Schnitt 39,9 Wochenstunden“ (Full-time employees worked an average of 39.9 hours per week in 2025). Press release, May 27, 2026.
Eurostat: „Average work week nearly 36 hours in the EU in 2025,“ May 27, 2026. Germany’s average was 33.9 hours actually worked per week across full-time and part-time employees.
Federal Statistical Office of Germany (Destatis): Explanatory information on Gross National Income (GNI) and its distinction from Gross Domestic Product (GDP).
John Rawls: A Theory of Justice (1971). German edition: Eine Theorie der Gerechtigkeit, translated by Hermann Vetter, Suhrkamp, Frankfurt am Main, 1975. Particularly the discussion of the difference principle.
Janine Höfler: „Wenn die KI ‚Daddy Cool‘ neu erfindet“ (When AI Reinvents „Daddy Cool“), Südwest Presse, August 26, 2026.
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