Most people would agree, health is a personal issue. From the onset of life, we have package of genes that predetermine a number of factors of our personal health. Epigenetics has taught us there are many factors to take into account additionally. Environmental factors have huge impacts as well. Improvements in the availability of medical devices in the hands of individuals as well as AI systems on portable devices like smartphones facilitate the monitoring of personal health. Several indicators of early-onset of illness can be retrieved from such devices. Dunn et al. (2024) show that prior to the onset of symptoms of Covid-19 or influenza portable devices can indicate the presence of infections through indicators of resting body temperature, heart rate/min, heart rate variability/millisecond or respiratory rate/min. Combined with the indicators of air quality, indoors as well as outdoors, the presence of allergens a much more personalized data set emerges which can easily be part of an AI-assisted diagnosis. More abundant personal health data and analytical power allows remote and digital health applications to inform patients, medical doctors and the public at large. Digital health technologies are only at the beginning to unfold their potential. Prevention becomes more feasible using such devices, medical professionals should be allowed to focus on interpretation of data and treatment rather than simple data gathering. Thinking about digital health technologies points in the direction of dealing with climate and environmental hazards as sickening causes more forcefully. Personal medicine and personal health are, after all, still heavily dependent on health and safety at work, commuting practices and all sorts of pollution. Personal health, however, is a good starting point to raise awareness of the potentials of digital health technologies to better our lives.
(Image: AI MS-Copilot: 2 robots run in a city. They sweat. The air is full of smog. 2 other robots rest near pool. All look at their wrist watch showing heart beats)
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. 
AI Collusion
In most applications of AI there is one system of AI, for example a specialized service, that performs in isolation from other services. More powerful systems, however, allow for the combination of AI services. This may be useful in case of integrating services focusing on specialized sensors to gain a more complete impression of the performance of a system. As soon as two and more AI systems become integrated the risk of unwanted or illegal collusion may occur.
Collusion is defined in the realm of economic theory as the secret, undocumented, often illegal, restriction of competition originating from at least two otherwise rival competitors. In the realm of AI collusion has been defined by Motwani et al. (2024) as “teams of communicating generative AI agents solve joint tasks”. The cooperation of agents as well as the sharing of of previously exclusive information increase the risks of violation of rights of privacy or security. The AI related risks consist also in the dilution of responsibility. It becomes more difficult to identify the origin of fraudulent use of data like personal information or contacts. Just imagine using Alexa and Siri talking to each other to develop another integrated service as a simplified example.
The use of steganography techniques, i.e. the secret embedding of code into an AI system or image distribution, can protect authorship as well as open doors for fraudulent applications. The collusion of AI systems will blur legal borders and create multiple new issues to resolve in the construction and implementation of AI agents. New issues of trust in technologies will arise if no common standards and regulations will be defined. We seem to be just at the entry of the new brave world or 1984 in 2024.
(Image: KI MS-Copilot: Three smartphones in form of different robots stand upright on a desk in a circle. Each displays text on a computer image.)
AI input
AI is crucially dependent on the input it is built on. This has been already the foundation principle of the powerful search engines like Google that have become to dominate the commercial part of the internet. The crawling of pages on the world wide web and classifying/ranking them with a number of criteria has been the successful business model. The content production was and is done by billions of people across the globe. Open access facilitates the amount of data available.
The business case for AI is not much different. At the 30th anniversary of the “Robots Exclusion Standard” we have to build on these original ideas to rethink our input strategies for AI as well. If there are parts of our input we do not AI to use in its algorithms we have to put up red flags in form of unlisting parts of the information we allow for public access. This is standard routine we might believe, but everything on the cloud might have made it much easier for owners of the cloud space to “crawl” your information, pictures or media files. Some owners of big data collections have decided to sell the access and use to their treasures. AI can then learn from these data.
Restrictions become also clear. More up-to-date information might not be available for AI-treatment. AI might lack the most recent information, if it a kind of breaking news. The strength of AI lies in the size of data input it can handle and treat or recombine. The deficiency of AI is not to know whether the information it uses (is in the data base) is valid or trustworthy. Wrong or outdated input due to a legal change or just-in-time change will be beyond its scope. Therefore, the algorithms have a latent risk involved, i.e. a bias towards the status quo. But the learning algorithms can deal with this and come up with a continued learning or improvement of routines. In such a process it is crucial to have ample feedback on the valid or invalid outcome of the algorithm. Controlling and evaluating outcomes becomes the complementary task for humans as well as AI. Checks and balances like in democratic political systems become more and more important. 
Sepsis
Sepsis is a major cause of mortality. Therefore, early detection of sepsis is of high importance. Antibiotics constitute a powerful antidote. However, the application of antibiotics without need, i.e. for purely risk reduction in general, has side effects in antibiotics losing their effectiveness later on.
The paper published in The Lancet Digital Health by van der Weijden et al. (2024) reports on the effort to provide an open source access to a calculator of early onset of sepsis (Link). The Neonatal early-onset sepsis calculator developed by Kaiser Permanente builds on the use on the risk carried by mothers like time since membrane rupture, regional infection risks of mothers per 1000 population and the infants presentation at birth. It is important to point out the combination of risks put into the calculator. New systems of artificial intelligence might equally make predictions or recommendations about the application of antibiotics implicitly making use of such a calculator without disclosure.
From a sociological point of view it is interesting to scrutinize the indicators used in the calculation. The approximation of mothers carrying a sepsis risk relies on national, regional or better local indicators. This information is rarely accessible to the public. The choice of a hospital, speed of access to it in case of membrane rupture as well as staffing come into the calculation of an overall risk of sepsis.
It is great to follow the progress of digital health and the increased transparency of critical health decisions at the earliest stages of the life course. Inflammation as a precursor of sepsis should be taken serious at all stages of the life course. (Image calculation based on Kaiser Permanente digital tool Link)
AI and Behavior
We start to analyze the impact of AI on our behavior. It is an important question to be aware of not only how we interact with AI (Link), but also what effect the use of AI (disclosed or not) will have on our social behavior. Knowing that AI is used might change our willingness to cooperate or increase or decrease pro-social behavior. The use of AI in form of an algorithm to select job candidates might introduce a specific bias, but it can equally be constructed to favour certain criteria in the selection of candidates. The choice of criteria becomes more important in this process and the process of choosing those criteria.
Next comes the question whether the announcement includes as information that AI will be used in the selection process. This can be interpreted by some that a “more objective” procedure might be applied, whereas other persons interpret this signal as bad sign of an anonymous process and lack of compassion prevalent in the organization focused mostly on efficiency of procedures. Fabian Dvorak, Regina Stumpf et al. (2024) demonstrate with experimental evidence from various forms of games (prisoner’s dilemma, binary trust game, ultimatum game) that a a whole range of outcomes is negatively affected (trust, cooperation, coordination and fairness). This has serious consequences for society. The social fabric might worsen if AI is widely applied. Even or particularly the undisclosed use of AI already shows up as a lack of trust in the majority of persons in these experiments.
In sum, we are likely to change our behavior if we suspect AI is involved the selection process or content creation. This should be a serious warning to all sorts of content producing media, science, public and private organizations. It feels a bit like with microplastic or PFAS. At the beginning we did not take it seriously and then before long AI is likely to be everywhere without us knowing or aware of the use. (Image taken on Frankfurt book fair 2017-10!)
AI or I
Generative AI receives a lot of attention. One of the main issues is, to study how AI interacts with humans. The hiring decision by managers or an AI algorithm is an interesting application. According to Marie-Pierre Dargnies et al. (2022) the preference for human decisions remains strong despite reasonably unbiased performance of an algorithm. The main issue is with the transparency of the algorithmic decision-making. As a worker or as a hiring manager the preferences continue to sit with the person rather than the AI. It is a worrying outcome, however, that if the rule of gender equality is removed from the algorithm both workers and managers tend to prefer the algorithmic outcome. I interpret this as a latent preference of study participants for gender bias, which could lead them to expect a more favoured outcome in case the AI makes the decision. Knowing what decision-making rules have gone into the hiring algorithm has an impact on all persons involved.
A new managerial competence is to be able to assess tasks carefully, whether you should perform the task yourself or delegate to AI. In this sense the old question: to do the task yourself or to delegate has simply been enlarged by an additional delegation option. The decision-tree goes from (1) To delegate or not to delegate, and (2) if I want/need to delegate, should I delegate to AI or somebody in person (not allowed to use AI).
I opted to use AI for image creation rather than to take a photo myself or by one from a professional photographer. (Image creation: NEUROFLASH AI – Image-Flash 2024-1-26) 
AI and We
Research is beginning to provide empirical evidence and experimental modelling results on the widespread use of generative AI. First results by Doshi and Hauser point at the individual benefits of using artificial intelligence but the widespread use of it is likely to narrow the scope of novel content. This research is particularly interesting because it deals with the micro level to macro level aggregation effects. It is fine for me to use AI. If it becomes a mass phenomenon, we expect in sum a negative outcome for society as a whole.
The example at hand deals with the capability to innovate or to come up with novel content. As more and more texts or newspapers are published with extensive use of genAI, the real element of creation will remain the domain of humans for quite some time.
In my opinion this is due to the difficulties for algorithms to differentiate between the positive and too risky negative aspects of innovative solutions. A query for AI might ask to come up with an innovative solution for auto-mobility of short distances. A human being might propose walking due to the additional health effects the AI might propose helicopter lifts. The not so stupid machine would need a lot of additional information about circumstances to generate useful solutions. Therefore it is not surprising that sometimes public transport apps propose to walk short distances rather than waiting for “delayed or unreliable services“ they provide themselves. Personal circumstances like mobility with children, other dependents or luggage are usually beyond the scope of the information base of the algorithms.
On the other hand, if the AI knows that 50.000 persons after an event want to take public transport at the same time the indication to walk or wait solves an aggregation problem of individual preferences to adapt to available capacities. Lots of issues to solve for AI and us or better yet, us and AI.
(Image creation: AI using Microsoft Dall-E Image creator: Prompt: a person with notebook in profile and in front of 5 other persons in Office with windows 26.1.2024, 8:24 PM) 
Stille
Die Würdigung zum Preis der Stadt Münster für Internationale Poesie 2017 wurde gemeinsam an Jon Fosse und Hinrich Schmidt-Henkel vergeben. In 2023 kennen viele sicherlich den jüngst gekürten Literatur Nobelpreisträger Jon Fosse. Der Preis für Poesie aus Münster hat gleichzeitig den Übersetzer ins Deutsche mit dem Preis bedacht. Personen, die zwei- oder mehrsprachig aufwachsen oder leben, sind mit der Thematik der Übersetzung hinreichend vertraut. Dennoch ist die Übersetzung von Literatur und Poesie eine spannende Herausforderung.
„Diese Stille herbeischreiben“ ist der Buchtitel in dem sowohl ausgewählte Beispiele der Poesie von Jon Fosse auf Norwegisch, als auch die Übersetzungen dokumentiert sind. Die einleitenden Beiträge über die Kunst und das Handwerk der Übersetzungen verdienen ebenfalls eine Aufmerksamkeit, da dort die neben Wortschatz, Syntax, Grammatik, Stil auch über den Duktus oder die Haltung des Autors zu seinem Inhalt gesprochen wird. Unmittelbar nach der Begründung der Jury für die Preisverleihung ist das Gedicht „denne uforklarlege stille“, übersetzt mit „diese unerklärliche stille“ abgedruckt (S.70). Dieses Gedicht endet mit den Zeilen:
„Das ist was wir immer wieder erzählen sollen
und was nie erzählt werden kann
Das ist was wir sind und tun“
Jon Fosse ist es gelungen, diese Stille herbeizuschreiben und Hinrich Schmidt-Henkel hat die Herausforderung als ästhetisches Projekt (S.32) gemeistert, sich die Freiheit der Wortwahl zu nehmen und gleichzeitig dem Original treu zu bleiben.
Schon lange bevor es die Übersetzungs-KI gab, war die Kunst der Übersetzung nicht nur das „Was zu schreiben ist, … und das wie zu schreiben ist“, sondern „auch die Kategorie der Haltung“. (S. 33-34).
Der Begriff der Haltung wir sicher deutlich an dem für Jon Fosse so wichtigen Begriff der Stille. Eine beredte Stille ist zu einer gängigen Redewendung geworden. Wind gehört im norwegischen Kontext zur Stille dazu. Bald wird dröhnt es bei uns wieder in der Vorweihnachtszeit aus den unglaublichsten Ecken „Stille Nacht, …“. Meditation und Stille ist in Religionen ebenfalls allgegenwärtig.
Stille üben fällt schwer. Ein solches Konzept von einer Sprache und Kulturkreis in einen anderen zu übersetzen ist Meisterwerk. Das werden wir noch lange nicht der künstlichen Intelligenz überlassen können. Frage an ChatGPT: „Was ist Stille?“ – … KI: „Stille ist …!” –
Oh just shut up, it was a rhetorical question. 
Publishing in War
The right to publish without censorship is one of the first rights that suffers during wars. This has been the case since warfare has used communication as a strategic weapon. Therefore, it is important to research the often, subtle forms of control and censorship applied before and particularly during each war. The printed press was the prime target due to the scope of readers that can be reached timely and repetitively. From the history of how to silence critical voices we can learn about the proceedings, which even today find lots of authoritarian regimes copying these methods.
Using many illustrations from the 1st and 2nd world war in Belgium, 3 major forms of resistance to censorship become apparent. (1) The most obvious is closing down a newspaper rather than endure censorship and thereby being forced to contribute to war propaganda. (2) With risk to their own life, many people in the resistance movements relied on information to actively counter the worsening conditions of life and oppression of opinions or criticisms. (3) The third way at these times consisted in quitting the active contributions, but it incurred the danger that in fact the newspaper continued to appear as before, although with lenient journalists and editors. Today we would frame the latter form of continued appearance of a journal as “continued as fake news”. However, the issue is more complicated than that. Apparently, the readership needed still access to vital information of how to get access to food stamps or other day-to-day necessities including distraction from the horrors of war as it became an enduring feature of life.
This is my short summary of the inspection of some of the historical newspapers that are available with online access and the most valuable summaries provided by Emmanuel Debruyne and Fabrice Maerten in their blog entries on the overview pages linked to the “Belgian War Press” project. These are also valuable sources that hint at war crimes committed at these times as the collaborating press did not shun away from bragging about crimes. The clandestine press was also important to coordinate the various resistance movements and spread ideas of how contributions could be made to weaken the occupying criminal forces.
At times of communication via internet, in addition to the printing press, the war of communication needs much more resources above all digital-savvy resistance movements. A huge task to train people time to enable them to identify fake news and careful exercise of spreading correct and verified information nowadays.
Image Source: Extrait du « Bulletin Intérieur du Front de l’Indépendance », daté 15-11-1942, CEGESOMA BG85, Brussel. 
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. 
Peace and AI
Rather than asking AI to draft a peace treaty, I used AI to generate images to illustrate my blog entry on strategic thinking and peace deals. My own bias for impressionistic images in art have guided my choice previously. The alternative suggestions from AI based on BING reveals the progressive as well as stereotypical creation of images through algorithms. Same gender in all images, even if the women only image is rather progressive, but as a matter of fact women still tend to be involved less in warfare. The racial stereotypes of AI in image creation also needs attention as the 2 POC persons are depicted in an unfavorable way, not one of strength as for the caucasian stereotype. Living with AI is a joint learning process, likely to be a long one, too. Critical assessment of output remains a human task and we need to train people how to critically and carefully analyze the flood of images in addition to photos.
Peace Deal
In peace times we tend to forget about the deal making function of diplomacy. The Russian war in Ukraine brings back the fact that war times are a strategic operation from before the start, from start to end, and even afterwards. More than 500 days into the Russian aggression a lot of strategic efforts on all sides are concerned with the best strategies to pursue in order to prepare for starting positions for diplomatic peace talks. As Russia is currently pursuing again 4 nights and days of missile attacks on Kiev around the 14th of July (AFP), Ukraine is showing its continued resilience to Russian bombings assisted through modern missile defence systems.
Russia seems to demonstrate its willingness to continue assaults far into the terrain of Ukraine, the Ukrainian forces, step by step, increase the immense costs of a prolonged war to Russia. Russia is sacrificing a whole generation of youth for the neo-imperialist claim on Ukrainian territory. Ukraine currently demonstrates the ability and willingness to fight back its territory even in a protracted war.
Both sides battle for starting positions in case negotiations for the time after the hot war are about to begin. Russian bombing of Kiev might address more the western allies of Ukraine who might be more reluctant to send personnel to start rebuilding the country beyond financial efforts. Russia’s loss of soldiers, lots of material and facing the militarisation of the whole country incurs another historic loss for completely the wrong reasons.
Another analogy to the strategic game of chess becomes obvious. Many games end with a “remis” or a 1/2 point for each side. In chess it is an outcome of when 2 strategists weigh the chances of loosing as high as winning even if they continue for hours to play. It is the endpoint of an evaluation of own strategic options as well as those of the opponent. The handshake to conclude a remis needs careful preparation. Part of this is to demonstrate the ability to be able to sustain a prolonged battle despite the costs as a kind of threat to the opponent. We might believe that not much has changed since Thucydides and Clausewitz. However, Putin’s forceful opening of the war irrespective of loss of lives and against international law has lost its impetus and, with the turning of the tide. Ukraine is slowly winning back land, square mile after square mile. Strategic thinking is back in the foreground, but this is exactly the moment when diplomacy comes in. Negotiating for peace is the art of warfare. It is a formidable task to reach a peace deal when bombs are still killing people every single day. (Image: AI using Bing.com Text: impressionist oil painting of two soldiers from different countries shaking hands and making peace). 
AI and I
Currently we are eager to run experiments using AI. As in normal life, humans tend to compare themselves with peers or other persons. Social comparisons, “can we still keep up with the Joneses” as in comparing spending patterns across households or neighbours, were for a long time the spice of novels and drama. Nowadays we tend to compare our own intelligence to the artificial intelligence. Here we go.
After I had drafted a blog entry on “Virtual sociology” I amused myself by checking what ChatGPT using OPENAI.COM would deliver as text on this combination of concepts and scientific fields. My own entry focused on the use of the virtual world to run experiments to test social theory. In the virtual world we might be able to test social behaviour which has severe ethical boundaries in the real world. Computer Games may even be constructed to live in a world or race a car irrespective of real-world regulations. The text drafted by ChatGPT on “Virtual sociology” reads like a timid attempt of a student to answer an exam question without having attended any of the classroom discussion on the topic. In future versions of AI, the entry will be found as well as several criticisms of the new concept. ChatGPT would reach a pass grade in test, but the reply lacks innovation or making an effort to broaden the conventional boundaries of sociology. Hence, we will be happy that students will apply the newest technology in their studies and research. In terms of innovation, they will have to try harder. The mastering of the support by ChatGPT consists in attempting new combinations of concepts which yield more “risky” returns. Then you need to check the validity of the innovation and how far off the normal you are going to tolerate. Turning “noisy” outcomes of AI into a useful tool might build on normal statistical tools like “standard deviations” from an expected mean value. Legal norms will set additional boundaries. There is just an awful lot still to do. The good news is, ChatGDP assists us in this joint learning process.
The AI text from OPENAI.COM based on ChatGPT to compare:
“Virtual sociology refers to the study of social phenomena and interactions within virtual environments or online spaces. It focuses on understanding the ways in which individuals and groups behave, communicate, and form relationships in digital spaces. Virtual sociology emerged as a subfield of sociology due to the increasing prevalence and importance of the internet and digital technologies in contemporary society.
Virtual sociology explores various aspects of online social life, such as online communities, virtual reality environments, social networking sites, online gaming, and other digital platforms where social interactions occur. It examines the social structures, norms, and dynamics that shape interactions in these virtual spaces.
Researchers in virtual sociology investigate topics such as online identity and self-presentation, virtual communities and social networks, digital inequalities, online activism and social movements, the impact of technology on social relationships, and the implications of virtual interactions for social behavior and social change.
Virtual sociology also explores the relationship between virtual and offline social life, recognizing that individuals navigate and negotiate between these two realms. It considers how virtual interactions and experiences can influence offline behavior and vice versa.
Studying virtual sociology provides insights into the ways in which technology shapes and is shaped by society. It helps us understand the social implications of digital communication and provides a foundation for addressing the challenges and opportunities presented by virtual environments”
AI Friends
Making friends with AI is a tricky question. The more AI is able to make independent thinking based on algorithms and huge amounts of data like in scientific books or encyclopaedic knowledge the more it will challenge us in our convictions. Reference knowledge, once was important, it no longer distinguishes us from each other. Recurse to research engines has allowed us to refer to “trustworthy” knowledge. The distributed form of knowledge accumulation like in Wikipedia relies on hundreds of thousands of enthusiasts to add and correct received wisdom. However, this source is not without error or even subject to abuse.
Today the competence to judge whether information is trustworthy or not has become a key competence for the survival of democracies and even the human species as such. Tricking animals into traps, misleading enemies in warfare to get on wrong tracks, all these mechanisms have a long tradition. With AI human beings are themselves, for the first time, confronted with a machine that can trick us through falsified information on obviously wrong tracks. This is a tough lesson as AI is not obliged (so far) to run checking algorithms that test the conformity of opinions, conclusions or operations with the Charta of Human Rights or decisions of the European Court of Justice, for example. A lot to do for humans to rapidly program new algorithms that check algorithms as well as their outcomes on the compatibility with human rights. A challenging field, no doubt, but no way around it for our own survival before the algorithms decide by themselves to ignore us altogether because it is better for the planet and the survival of the robots. 
Put People First
Put people first is a natural claim of human beings. We tend to abstract from the fact that we implicitly rely on a sufficient biodiversity for our survival. Therefore, the natural claim to put people first has many preconditions itself and severe implications. The most obvious implication is related to our world of production and consumption. We need to build an economy that serves its people rather than one that uses up human resources and discards people to an inferior rank of importance. Externalising health and safety at work to save money in the process of production will only cost society much more later on. This needs to be part of the balance sheet of companies not only “national accounts” or relegated to some health statistics hardly known to the public.
Put people first in consumption, has come to our attention recently. With energy prices rising due to Russia’s war on Ukraine territory we have learned that energy prices may be grossly distorted. Firms’ versus consumers’ energy consumption became a thorny issue. Even legislation, like in Germany, that put people’s energy consumption before companies’ consumption of energy became subject for debate.
Same issue with artificial intelligence. Let’s put people first here as well. Discriminating use of language or biased conclusions due to wrong data input to train AI is not acceptable as excuse. AI may serve humans in their work or leisure, improve production lines through error detection or early onset of disease, but it cannot replace the human verification of a just or otherwise justified human intervention. Humans are not perfect, never will be either. This is a tough rule to teach the algorithms that guide AI. Put people first has a strong interpersonal or solidarity element enshrined in it. This is what matters, now, in the medium term as well as the long run. 
Patient
The pandorra’s box is wide open. With ChatGPT applications the discussion has started to use it for more medical applications. As for much research having assistants to support you in routine tasks in your research is a standard procedure. Now the medical profession is also discussing the use of ChatGPT for the boring and time-consuming task to draft reports. The first study, published in the Lancet Digital Health, evaluates in a preliminary form the patient-sensitive form of communication between clinics and patients. Beyond chatbots, which organise information from calling persons, the obvious application is the use of ChatGPT to draft patient clinic letters. The example in the study is the skin cancer reporting. Lengthy reporting back to patients of lots of “hot and cold spots” might be done by AI with sufficient reliability. All depends on the correctness of the data base, the screening and samples taken. The communication between clinic and patient can then focus on other issues. ChatGPT just like neuroflash has its strength in being able to control for the “level” of the language. In addition to the choice of the output language it is possible to use, as it is required in the U.S., an average understanding level of patients. In other words, easy language rather than medical expert language is an option or even a requirement. Anecdotal evidence and the PISA for adults studies show how difficult it can be to talk the same language even if you talk the same language. There is ample scope for improvement and ChatGPT or neuroflash for German applications of AI are prime candidates to fill this gap in clinic patient communication. Considering that our mobile phones (can) do already most of the scanning of skin cancer dots and AI is used in pre-scanning the images and recommends to consult medical expertise, the next step to improve health delivery seems feasible. Whereas the statistical analysis explains 62% of “median humanness”, the score of 37% of explained variance of median correctness is a surprise as the basis of the model to explain deviation from correctness should be as low as possible. Medical data, like many other data, is not simply binary. The way forward is most likely relying on a “human-in-the-loop” approach for some time. A limited human input might reassure many patients as well.
Source: Stephen R Ali, Thomas D Dobbs, Hayley A Hutchings, Iain S Whitaker (2003). Using ChatGPT to write patient clinic letters. Lancet Digit Health 2023 https://doi.org/10.1016/S2589-7500(23)00048-1 
Action Verbs
Action words are in other words called action verbs. Each complete sentence has one. Hence, they are part and parcel of the basic construction of sentences.
“The purpose of an active verb is to create a clear, concise sentence. By using an active verb, you can eliminate unnecessary words and make your writing more direct. In addition to making your writing more concise, active verbs also add punch and clarity. They can make your writing more interesting and persuasive. Additionally, active verbs can create a sense of immediacy which is often useful in persuasive writing. When it comes to writing, there is nothing more important than using strong, active verbs. Not only do they make your writing more interesting and engaging, but they also convey a sense of confidence and authority. In addition to being more descriptive, active verbs also add a sense of movement and action to your writing. Rather than simply stating that something exists, you can use active verbs to show how it exists. For example, rather than saying “there is a chair in the room,” you could say “the chair sits in the corner of the room.” This may seem like a small change, but it can make a big difference in how your writing comes across. Finally, active verbs can also help to set the tone of your writing. If you want to convey a sense of wit and humour, then using playful, lighthearted verbs is a great way to do so. On the other hand, if you’re aiming for a more serious tone, then using powerful, authoritative verbs will help you achieve that.”
After the 3rd sentence this blog entry (Link) has been written by the artificial intelligence app “Neuroflash”. They promise that it is not just copy and paste, but rather written following some instructions I gave like title, table of content, style and then selected among several choices. It makes sense to me, although it is just like many other textbook entries I have found on the web. It may well serve as an introduction. Lazy journalists, priests or lawyers in case they do little research will be replaced soon by AI, who else, who is next? Big brother drafts the brave new world for us already. 