It has become a common starting point to use electronic devices and online encyclopedias to search for definitions. Let us just do this for artificial intelligence. The open platform of Wikipedia returns on the query of “artificial intelligence” the following statement as a definition: “AI … is intelligence exhibited by machines, particularly computer systems …“. It is not like human intelligence, but tries to emulate it or even tries to improve on it. Part of any definition is also the range of applications of it in a broad range of scientific fields, economic sectors or public and private spheres of life. This shows the enormous scope of applications that keeps rapidly growing with the ease of access to software and applications of AI.
How does AI define itself? How is AI defined by AI? Putting the question to ChatGPT 3.5 in April 2024 I got the following fast return.
(See image). ChatGPT provides a more careful definition as the “crowd” or networked intelligence of Wikipedia. AI only “refers to the simulation” of HI processes by machines”. Examples of such HI processes include the solving of problems and understanding of language. In doing this AI creates systems and performs tasks that usually or until now required HI. There seems to be a technological openness embedded in the definition of AI by AI that is not bound to legal restrictions of its use. The learning systems approach might or might not allow to respect the restrictions set to the systems by HI. Or, do such systems also learn how to circumvent the restrictions set by HI systems to limit AI systems? For the time being we test the boundaries of such systems in multiple fields of application from autonomous driving systems, video surveillance, marketing tools or public services. Potentials as well as risks will be defined in more detail in this process of technological development. Society has to accompany this process with high priority since fundamental human rights are at issue. Potentials for assistance of humans are equally large. The balance will be crucial.
Wage Minimum
A wage at a minimum level is frequently lower than the minimum wage. Most EU countries have a legal minimum wage that should protect against poverty risks at low levels of wages. Over decades it has not yet been possible to raise all low wages to this level. Le Monde (Béatrice Madeline et Aline Leclerc) has published on April 3rd a comprehensive analysis of sectors and people concerned with this difficulty to make a decent living while earning the minimum wage. In France (La désmicardisation), as in many other countries, it is difficult to earn just a bit more as the minimum wage because both employers and employees may lose social benefits if they just earn some hundred € more than the legal minimum wage. For all those persons who do receive only a wage even below the minimum wage getting stuck in a poverty trap is very likely. The number of working hours is then often is the only option to make ends meet your needs. Put bluntly, you work additional hours and/or take a second job to complement the lack of earning a wage at the minimum level. Public procurement that makes the application of the minimum wage compulsory and controls this application effectively benefits society as a whole. Lots of infrastructure projects, urban and rural development receive public support. The conditionality to pay the minimum wage + X should be a „conditio sine qua non“. The millions of workers at the lower end of the wage distribution have a power at the ballot box, which continues to be underestimated in many European countries. The EP elections on June 9th will probably alert us about the lack of faith in a bettering of living and working conditions of those persons coping with wage minima.
Architecture Berlin
The annual exhibition of completed architecture projects in Berlin attracts people beyond the narrow circles of architects. You may take a walk through Berlin to view the actual realizations in 3D or 4D with people living, working or moving in these buildings. As social scientists we like talking or interviewing these people about their experiences. Urban planning and participation in urban development is important for city development in a democratic fashion. The combination of social, ecological, economic and technological concerns find compromises in urban renewal. The range of activities is remarkable. Living spaces have the most entries in the exhibition followed by offices and trade spaces. Education as well as public open spaces raise a lot of interest and funding currently. Climate change and adaptation to limited ecological resources ask for innovative solutions as well. Most projects in Berlin or by Berlin based architects deliver in this respect. The socio-ecological change needs a lot of actors to implement such changes and meet unprecedented challenges. The 60 projects represented for 2023 are the top of the iceberg but a lot remains to be accomplished in repairing old buildings and infrastructure as well. The DA! exhibition provides a democratic transparency of projects, which allows the public to learn about innovation and to make more informed judgments about what architecture can deliver for society.
Russian Angst
The title of a book “Russian Angst” by Thomas Franke summarizes the state of Russian society under Putin. It dates back to 2017, but the underlying process of Angst in the Russian society is increasing rather than diminishing due to the already 2 years long intensive hot war of Russia against Ukraine. The Russian Angst is a fear of a continued roll back of its authoritarian rule in Eastern parts of the world and its internal threat that its own people will claim more rights like freedom of speech, freedom of the press and effective democratic voting rights. In a dictatorship the “Angst” is a pervasive phenomenon which creeps into all spheres of live. Franke and Dornblüth (2023) describe the toxic society in Russia. Intoxication and torture of opponents are used by the Putin regime as a threat to suppress critical voices in Russia. Through this a climate of “Angst” is spread so that any internal opposition has to face very high risks to utter any discontent. The experience of a barbarian, totalitarian regime is well known. The threat to life and the presence of intimidation to any disobedient behaviour are strictly persecuted. Nevertheless, the need to think beyond the Putin regime is well under way. The more external and internal, real or imagined threats are countered with brutal force, the more the regime reveals its true kind of governance by force. This invites and leads to the strengthening of counter forces both internally and externally. It seems like box fight in the before last round of a very vulnerable, weakened and isolated boxer. Not many will bet on the likely loser and more countries who previously supported Putin will stop their erroneous policy. Russian Angst and loneliness will further increase. 
AI Sorting
Algorithms do the work behind AI systems. Therefore a basic understanding of how algorithms work is helpful to gauge the potential, risks and performance of such systems. The speed of computers determines the for example the amount of data you can sort at a reasonable time. Efficiency of the algorithm is an other factor. Here we go, we are already a bit absorbed into the the sorting as purely intellectual exercise. The website of Darryl Nester shows a playful programming exercise to sort numbers from 1 to 15 in a fast way (Link to play sorting). If you watch the sorting as it runs you realize that programs are much faster than us in such simple numeric tasks. Now think of applying this sorting routine or algorithm to a process of social sorting. The machine will sort social desirability scores of people’s behavior in the same simple fashion even for thousands of people. Whether proposed AI systems in human interaction or of human resource departments make use of such sorting algorithms we do not know. Sorting applicants is a computational task, but the data input of personal characteristics is derived from another more or less reliable source. Hence, the use of existing and newly available databases will create or eliminate bias. Watching sorting algorithms perform is an important learning experience to be able to critically assess what is likely to happen behind the curtains of AI.
AI and dialect
The training of Large Language Models (LLM) uses large data sets to learn about conventions of which words are combined with each other and which ones are less frequently employed in conjunction. Therefore, it does not really come as a surprise that training which uses standardised languages of American English might not be as valid for applications that receive input from minority languages or dialects. The study forthcoming in the field of Computer science and Language by Hofmann et al. (Link) provides evidence of the systematic bias against African American dialects in these models. Dialect prejudice remains a major concern in AI, just like in the day-to-day experiences of many people speaking a dialect. The study highlights that dialect speakers are more likely to be assigned less prestigious jobs if AI is used to sort applicants. Similarly, criminal sentences will harsher for speakers of African American. Even the more frequent attribution of death sentences for dialect speakers was evidenced.
If we translate this evidence to wide-spread applications of AI in the workplace, we realise that there are severe issues to resolve. The European Trade Union Congress (ETUC) has flagged the issue for some time (Link) and made recommendations of how to address these shortcomings. Human control and co-determination by employees are crucial in these applications to the world of work and employment. The need to justify decision-making concerning hiring and firing limit discrimination in the work place. This needs to be preserved in the 21st century collaborating with AI. The language barriers like dialects or multiple official languages in a country ask for a reconsideration of AI to avoid discrimination. Legal systems have to clarify the responsibilities of AI applications before too much harm has been caused.
There are huge potentials of AI as well in the preservation of dialects or interacting in a dialect. The cultural diversity may be preserved more easily, but discriminatory practices have to be eliminated from the basis of these models otherwise they become a severe legal risk for people, companies or public services who apply these large language models without careful scrutiny.
(Image AI BING Designer: 3 robots are in an office. 2 wear suits. 1 wears folklore dress. All speak to each other in a meeting. Cartoon-like style in futuristic setting) 
Sleeping BPS-SPB
Sleeping is a good example of the co-determination of the biological, psychological and societal spheres of life. The environment with the daily cycles of light and dark as well as the social norms of work and rest determine the circadian cycles of hormones. Shift work or otherwise disrupted sleep patterns depend on social norms like regulation of noise or light in cities. Healthy sleep patterns, therefore, depend to a large amount on regulation and implementation of those social norms. Birthday parties are tolerated, but much less the irregular partying in shared housing with lots of neighbours. Reducing social contacts during Covid-19 led to the changes in sleep patterns as well.
The psychological determinants of sleep go well beyond the world of dreams as theorized by Freud. Nowadays, we investigate all sorts of behavioural patterns that have an impact on sleeping like “bedtime technology use” of smartphones or the ability to switch off thinking of problems. Sleeping is a particular functional state of our mind. A lot of sorting of daily impressions into memory occurs during the different phases while sleeping. Persistent disrupted or impeded sleep is recognized as torture in severe cases. Stress at work or working overtime is also a major cause of sleep disorders.
The biological indicators used to investigate sleep have revealed a lot of links of sleep and the hormones of melatonin as well as cortisol. Testing has become more accessible and provides good indicators of how the biological clocks tick within our bodies.
However, we are only at the beginning of the analysis of more complex interactions of the multiple forms of interaction of the bio->psycho->social (BPS) as well as the social->psycho->bio (SPB) co-determination of sleeping. Scientific research is faced with a steep challenge as the direction of causality is not uniform except in very controlled experimental settings. Maybe the arts have coined and popularized a useful term in this respect. “I am in a New York state of mind”.
(Image: extrait of Magritte. La clairvoyance, 1936 and The cultural context of aging, Jay Sokolovsky) 
AI and S/he
There was hope that artificial intelligence (AI) would be a better version of us. Well, so far that seems to have failed. Let us take gender bias as a pervasive feature even in modern societies, let alone the societies in medieval or industrial age. AI tends to uphold gender biases and might even reinforce them. Why? A recent paper by Kotek, Dockum, Sun (2023) explains the sources for this bias in straightforward terms. AI is based on Large Language Models. These LLMs are trained using big detailed data sets. Through the training on true observed data like detailed data on occupation by gender as observed in the U.S. in 2023, the models tend to have a status quo bias.
This means they abstract from a dynamic evolution of occupations and the potential evolution of gender stereotypes over years. Even deriving growing or decreasing trends of gender dominance in a specific occupation the models have little ground for reasonable or adequate assessment of these trends. Just like thousands of social scientists before them. Projections into the future or assuming a legal obligation of equal representation of gender might still not be in line with human perception of such trends.
Representing women in equal shares among soldiers, 50% of men as secretaries in offices appears rather utopian in 2024, but any share in-between is probably arbitrary and differs widely between countries. Even bigger data sets may account for this in some future day. For the time being these models based on “true” data sets will have a bias towards the status quo, however unsatisfactory this might be.
Now let us just develop on this research finding. Gender bias is only one source of bias among many other forms of bias or discriminatory practices. Ethnicity, age or various abilities complicate the underlying “ground truth” (term used in paper) represented in occupation data sets. The authors identify 4 major shortcoming concerning gender bias in AI based on LLMs: (1) The pronouns s/he were picked even more often than in Bureau of Labor Statistics occupational gender representations; (2) female stereotypes were more amplified than male ones; (3) ambiguity of gender attribution was not flagged as an issue; (4) when found out to be inaccurate LLMs returned “authoritative” responses, which were “often inaccurate”.
These findings have the merit to provide a testing framework for gender bias of AI. Many other biases or potential biases have to be investigated in a similarly rigorous fashion before AI will give us an authoritarian answer, no I am free of any bias in responding to your request. Full stop. 
Flipbook
We all enjoy books that are real page turners. Nowadays, we still enjoy the virtual impression of turning pages when we read. Okay, that is a bit old school, I believe. For all those who prefer to hold a page turning book in their hands it is about time to try the e-versions of flipbooks. You may include the sound of turning a page just as in the real book format. Alternatively, you may listen to your favourite music on the same device.
For that reason the chronological blog entries are also available as Flipbooks.
It is still in test runs, so don’t hesitate to send me feedback at klaus(at)schoemann.org
The data base has grown rapidly. Take your time to scroll and read.
2024 January – February.
2023 September – December
2023 May – August
2023 January – April
Bigger screens allow for more comfortable reading, but make sure your eyes do not suffer too much. Adjust the light as low as possible for more relaxed reading. Print formats are evolving and so does the concept of a book or a reader. The content is the conceptual idea. The appropriate form for the content is a matter of an additional choice. Not only books have changed to electronic versions. Libraries are also adapting to the new forms of reading on screens and co-working. Flipbooks are a kind of hybrid version satisfying a readership in transition before endless scrolling will take over. The content is key and the rest is POSSE.
Error 444
The error message 444 is a not so rare encounter while surfing on the web. The error code 444 stands for the message that from the side of the server the connection is closed without any additional message. The occurrence leaves you without further indication of what exactly went wrong in building a connection to a web service or website. You just simply get shut out and that’s it. It may be tough on you if concerns your online banking or other access to vital services delivered through the internet.
In organization science and social science there are many new studies dealing with the finding, dealing, coping or handling errors. It has become much more acceptable to deal openly with errors, blunders or failures. From an individual as well as organizational perspective the cultures that deal openly with these events seem to have a certain advantage to overcome the consequences of errors at all or faster than others.
In some biographies failures are part of the lessons learned throughout life. It is deemed important to acknowledge failures or paths not taken for better or worse. Organizations just like individuals seem to learn more intensively from their failures or omissions than from everything seemingly running smoothly. Learning curves are faster also for “machine learning” if you have access to a huge data set which contains ample data on failures rather than encountering failures after release. Hence, the compilation of errors is an important part or early stage of a learning process. Failed today? Fail again tomorrow. You’ll be really strong the days after although it might hurt. 
Barbie explore
The film on Barbie after more than 60 years of the first puppets to arrive on the market is a huge money spinning exercise. Hitting more than 1 billion $ is really a huge box office success. More interesting even is the banning of the film in some countries like Algeria. This gives the film an interesting subversive touch to it, which we in the Western countries no longer see as something special. Emancipated women pose a threat to authoritarian regimes.
However, we see in the stereotypes of beauty-driven dolls not that much of an emancipatory chance. To view emancipation independent of the looks of a person is another interesting twist to the role in stereotypes of beauty. It is not only fun to play around with stereotypes, that is mostly, if you are not negatively affected by them (age, gender, ethnicity, extraordinary persons). A nice task for sociology and psychology to explain the working of stereotypes in society and possible remedies. Tolerance is a competence that needs to be learned and updated continuously, from early age onwards.
Therefore, the website created by the US Design Agency Rvnway offers an entertaining way to play around and learn about stereotypes. Perceived, generalized beauty or gender roles can be explored using the tool. Maybe some see themselves differently after such explorations. Everybody is a model. This is the message. www.bairbie.me will let you explore other formats of yourself. After 3-D rendering and printing your children or grandchildren will decide what role they would like you to play in their playfull, or virtual “real” life. I suppose many of us will be up for a big surprise. Go on and imagine in 4D. In the age of selfies all around us, all the time, we believe we are very modern, but the artists of the 19th and 20th century following all great painters before, frequently started their careers with an “autoportrait” or “Selbstbildnis” or series of those as they were aging. 
