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AI indicators

AI in work and society

What are the developments and trends in AI applications that we observe in the labour market, workplace, work organisation and society? To understand the developments and consequences of AI and respond in scientific or policy terms, we need key figures. The AI Observatory is continuously further developing this selection. For this reason, we are always interested in suggestions and ideas about additional indicators.

 

The use of AI applications in the workplace and the consequences for employees are of major importance. Specific AI indicators can provide information about job security in the context of this technological development, how AI is changing the everyday work of employees, which changes employees anticipate from the use of AI in the workplace and which consequences they fear.

The majority does not anticipate losing their jobs

The security of jobs is frequently discussed in relation to the impacts of AI on the workplace; indeed, the acceptance of AI is largely dependent on it. The indicator featured here shows how likely those who took part in a representative survey (sample: above 18 years of age in Germany) believed the loss of a job would affect (a) themselves, (b) persons from their immediate environment or (c) members of social minorities and disadvantaged groups. The latter group includes people with a migrant background, those with disabilities or single parents.

Overall, only a small number of respondents expect revolutionary changes on the labour market in the next five years. Around 11% of the respondents believe that more new jobs will be created than replaced. The respondents see themselves as being least at risk of losing their job: only 6% believe that AI is likely or very likely to lead to the loss of their occupation. Roughly 20% anticipate the threat of mass unemployment while a slightly lower number believes that family members, friends and acquaintances could lose their job (18%). The insights gained from this indicator contradict the common thesis in debates that many people are fearful of the use of AI.

The key findings of the BMAS Skilled Labour Monitoring show that, compared with the present day, 1.4 million jobs will no longer exist in five years’ time but at the same time that 1.3 million new jobs will also be created. Assumptions regarding a digitalised workplace, the demographic change, the transition to a carbon-neutral economy as well as the consequences of the COVID-19 pandemic are taken into account in this case.

AI definition: The respondents of this survey were not provided with a definition of AI. Therefore, the answers given by the respondents are based on their current perception of AI.

Methodology: The data on which the indicator is based was collected by the project “Opinion Monitor Artificial Intelligence [MeMo:KI]” conducted by the Centre for Advanced Internet Studies and the University of Düsseldorf in cooperation with the AI Observatory as part of a special survey on the topic of “AI in the Workplace”. The survey was conducted by forsa Politik & Sozialforschung GmbH as an online questionnaire among persons who were over 18 years of age and used the Internet at least occasionally. This was a random sample of 1,001 respondents who were weighted according to the criteria of age, gender and region (by German federal state) (60% of whom were employed, 51% female, 32% between 18 and 39 years of age, 64% with a (technical vocational) school diploma, 53% with a net household income of €3,000 or more). The survey was conducted during the period from 24/08 - 28/08/2020. The content of the survey focussed primarily on expectations in a professional context in conjunction with AI, which referred to the respondents themselves. The respondents could respond using a scale of 1 (very unlikely) to 5 (very likely). The diagram summarizes the answers to values 1 and 2 on the scale as well as to values 4 and 5. You can find additional information about the survey on the subject of “AI in the Workplace”, about the MeMo:KI project and the Detailed Methodology Overview in the corresponding links.

The greatest changes driven by AI are expected in the areas of data security and skills requirements

How does the use of AI impact on everyday work? How aware is the population of possible changes to people's tasks in the workplace as a result of AI? Based on a representative survey of employees in Germany, this indicator shows what expectations they associate with the use of AI, and how they believe the use of AI will affect their working conditions.

The survey data reveals that more than half of the respondents expect only some changes (3) or if anything no changes (1&2) to most working conditions. The greatest changes presumed by the respondents relate to the security of their data (42%) and regarding the skills required at their workplace (38%). In particular regarding the development of income (16%), co-determination (20%), job satisfaction (21%) as well as career opportunities (21%), only a small proportion of the respondents believe that the introduction of AI into the workplace will change anything for them in the medium term.

According to the researchers behind the MeMo:KI study, experts believe it is likely that AI will lead to changes across a range of areas. This indicator raises the question as to why the employees surveyed generally assessed the potential for changes to their own working conditions as rather low and very differently for a range of other working conditions. This may be due to varying degrees of awareness of different changes.

AI definition: The respondents of this survey were not provided with a definition of AI. Therefore, the answers given by the respondents are based on their current perception of AI.

Methodology: The data on which the indicator is based was collected by the project “Opinion Monitor Artificial Intelligence [MeMo:KI]” conducted by the Centre for Advanced Internet Studies and the University of Düsseldorf in cooperation with the AI Observatory as part of a special survey on the topic of “AI in the Workplace”. The survey was conducted by forsa Politik & Sozialforschung GmbH as an online questionnaire among persons who were over 18 years of age and used the Internet at least occasionally. This was a random sample of 1,001 respondents who were weighted according to the criteria of age, gender and region (by German federal state) (60% of whom were employed, 51% female, 32% between 18 and 39 years of age, 64% with a (technical vocational) school diploma, 53% with a net household income of €3,000 or more). The question on which the indicator is based was addressed to employees only. The survey was conducted during the period from 24/08 - 28/08/2020. The content of the survey focussed primarily on expectations in a professional context in conjunction with AI, which referred to the respondents themselves. The respondents could respond using a scale of 1 (no change) to 5 (very significant change). The diagram summarizes the answers to values 1 and 2 on the scale as well as to values 4 and 5. You can find additional information about the survey on the subject of “AI in the Workplace”, about the MeMo:KI project and the Detailed Methodology Overview in the corresponding links.

Lack of transparency about data use (50%) and surveillance at the workplace (40%) are cited as the most feared consequences of AI

The use of AI at the workplace presents opportunities but also challenges. This indicator shows which consequences of AI in the workplace employees fear. Here too, the data is based on a representative survey conducted among adult employees older than 18 years of age in Germany.

In particular, a lack of transparency about data use (50%) and surveillance at the workplace (40%) are singled out as the most feared consequences. On the other hand, only 11% of respondents feared that their qualification might no longer be sufficient to meet their job requirements and only 10% that they will be overburdened by the use of AI in their industry.

This indicator supplements the indicator “Assessment of change within people’s own workplace due to AI” and underlines that those affected are most concerned about the area of data security. Although changed job requirements are expected (see above), they are only feared by a small proportion of employees.

AI definition: The respondents of this survey were not provided with a definition of AI. Therefore, the answers given by the respondents are based on their current perception of AI.

Methodology: The data on which the indicator is based was collected by the project “Opinion Monitor Artificial Intelligence [MeMo:KI]” conducted by the Centre for Advanced Internet Studies and the University of Düsseldorf in cooperation with the AI Observatory as part of a special survey on the topic of “AI in the Workplace”. The survey was conducted by forsa Politik & Sozialforschung GmbH as an online questionnaire among persons who were over 18 years of age and used the Internet at least occasionally. This was a random sample of 1,001 respondents who were weighted according to the criteria of age, gender and region (by German federal state) (60% of whom were employed, 51% female, 32% between 18 and 39 years of age, 64% with a (technical vocational) school diploma, 53% with a net household income of €3,000 or more). The question on which the indicator is based was addressed to employees only. The survey was conducted during the period from 24/08 - 28/08/2020. The content of the survey focussed primarily on expectations in a professional context in conjunction with AI, which referred to the respondents themselves. The respondents could respond using a scale of 1 (I do not agree at all) to 5 (totally agree). The diagram summarizes the answers to values 1 and 2 on the scale as well as to values 4 and 5.

AI specialists and their skills are very much in demand. It is therefore essential to understand the situation of employees with AI skills in the labour market. How many people in Germany can program, use and control AI? How does Germany rank internationally in terms of its number of AI specialists? Which AI skills are currently particularly in demand – expertise in machine learning, deep learning or another area? The indicators shown in the “Skills” thematic area provide initial answers to these questions.

Machine learning: the undisputed number one AI skill in Germany

Which AI skills are particularly sought-after and relevant in Germany? Two indicators are used to answer this question. The first indicator shows which skills were the most frequently added AI skills among LinkedIn users in Germany during the years 2015-2020. The second indicator reveals the AI skills for which the frequency of mention by LinkedIn users (in the annual comparison) showed the highest percentage increase during the same period.

Among the most common AI skills (first indicator), machine learning has been the undisputed number one since 2015. However, artificial intelligence (see the notes regarding the methodology) and deep learning are to be found among the top-ranked positions.

Turning to the greatest changes in mention of AI skills in the annual comparison (second indicator), what is striking is that both the sequence as well as the skills change utterly almost every year. Whereas the three most important AI skills in 2019 were pattern recognition, language recognition and convolutional neural networks, they were data structures, Pandas (software) and Julia (programming language) in 2020. This indicator paints a clear picture of which skills are behind the commonly used term “AI skills” – especially in Germany.

Top AI skills by frequency (2015-2020) (Germany)

AI skills that were most frequently added by LinkedIn users in Germany during the years 2015-2020

  1. Machine Learning
  2. Artificial Intelligence (AI)
  3. Deep Learning
  4. Computer Vision
  5. Image Processing
  6. TensorFlow
  7. Natural Language Processing (NLP)
  8. OpenCV
  9. Keras
  10. Neural Networks

LinkedIn Economic Graph, December 2020

Note: LinkedIn data does not represent a randomised sample of the working population of a country. It is based on statements by LinkedIn users and as such does not necessarily represent all economically active persons in a country, even if a high proportion of those in many countries are LinkedIn users. The analyses presented here show the world from the perspective of LinkedIn, i.e. results are influenced by who uses LinkedIn and how. Depending on the country, this may be different and is influenced by various factors such as professional, socio-economic, regional or cultural background. In Germany, less than 40% of the working population are on LinkedIn.

AI definition: The definition of AI skills presented here covers a list of skills that were identified by LinkedIn as AI skills. This list includes machine learning, natural language processing, data structures, artificial intelligence, computer vision, image processing, deep learning, TensorFlow, Pandas (software) and OpenCV. The complete list of AI skills is the property of LinkedIn and is not publicly available. For more information about the LinkedIn Skill Group Classification, see also: World Bank Group, LinkedIn (2018), Data Insights: Jobs, Skills and Migration Trends Methodology & Validation Results, Appendix F.

Methodology: Top AI skills by frequency: The data underpinning this indicator relates to the ten most frequently mentioned AI skills on average by LinkedIn users in Germany in the years 2015-2020. Artificial intelligence is also one of the second most frequently added skills by LinkedIn users to their profile between 2015 and 2020. Even though this skill falls under the umbrella term of the AI competence group, it exists as a separate skill at LinkedIn because LinkedIn users specify it as such on their profiles. LinkedIn’s skills taxonomy is derived from the skills that LinkedIn users specify. These are audited by LinkedIn, verified as actual skills and then standardised, which means that the skills taxonomy is largely generated by users. Top AI skills based on the highest year-on-year change: the ten skills that had the highest percentage growth of LinkedIn users in Germany who added these skills to their profiles during the years in question. Further information can be found in the methodological note of the OECD AI Policy Observatory (OECD.AI).

Only 21% of AI talents in Germany are women

AI experts are highly sought-after on the labour market. Companies, universities and research institutions face major challenges in recruiting qualified employees to fill vacancies in the field of AI. How many AI talents are there in Germany and other countries? And how are women represented in this forward-looking area? In which industries do AI talents work in Germany?

This indicator shows the number of AI talents in Germany, the USA, the United Kingdom, France, Switzerland, the Netherlands and Denmark. In Germany, a total of 143,000 LinkedIn users were identified as AI talents. The absolute number of AI talents in the countries cannot be compared directly because the number of those economically active in the countries is different, the proportion of LinkedIn users out of the total working population varies and because industries and labour market areas are represented on LinkedIn to differing degrees depending on the country.

Even if the numbers are not directly comparable internationally, LinkedIn assumes that AI trends are clearly represented on the platform since its members have an affinity to the digital domain. It is clear that even more needs to be done to promote women in the field of AI. The proportion of women among AI talents in Germany is relatively low compared with the other countries. Only 21% of the AI talents in Germany are women. In the USA, 28% of AI talents are women while the equivalent in the United Kingdom is 27%. In Germany, the majority of AI talents work in the ICT industry (31% compared with 12% of all LinkedIn users in Germany).

Note: LinkedIn data does not represent a randomised sample of the working population of a country. It is based on statements by LinkedIn users and as such does not necessarily represent all economically active persons in a country, even if a high proportion of those in many countries are LinkedIn users. The analyses presented here show the world from the perspective of LinkedIn, i.e. results are influenced by who uses LinkedIn and how. Depending on the country, this may be different and is influenced by various factors such as professional, socio-economic, regional or cultural background.

AI definition: AI talents are defined as any LinkedIn user who explicitly lists one of the AI skills identified by LinkedIn on his/her LinkedIn profile or who mentions one of the job titles defined by LinkedIn as an AI job. Examples of the skills identified by LinkedIn as AI skills include machine learning, natural language processing, data structures, artificial intelligence, computer vision, image processing, deep learning, TensorFlow, Pandas (software) and OpenCV. Examples of AI jobs include machine learning engineer, artificial intelligence engineer and computer vision engineer. The complete list of AI skills and AI jobs is the property of LinkedIn and is not publicly available.

Methodology: The data shown here represents the level of data at LinkedIn at a specific time in December 2020. Based on LinkedIn’s economic graph, the LinkedIn users in the countries mentioned represent at least 40% of the working population, which vouches for the quality of the data. However, the quality of data for Germany is lower than the rest of the data due the lower penetration of LinkedIn among the working population. Although LinkedIn users do not specify their gender classification, this is derived from the first names of LinkedIn users. LinkedIn uses software that it programmed itself to perform this identification. The reporting industries in indicator 5.2. correspond to the classification used by LinkedIn. The assignment of LinkedIn industries to the Statistical Classification of Economic Activities in the European Community (NACE) can be helpful in classifying the LinkedIn sectors.

High demand for AI talents in Germany

The demand for more AI talents and AI skills is frequently a subject of discussion. It was also the subject of a study from 2019, which was commissioned by the Federal Ministry for Economic Affairs and Energy and conducted by the Leibniz Centre for European Economic Research. The study confirms the existence of strong demand for AI experts: 30% of companies that use AI in Germany had vacancies to fill in this field in 2019.

What picture emerges regarding the hiring rates of AI talents in other OECD countries? This indicator shows that the hiring rate of AI experts in Germany in 2020 was 1.58 times greater than in 2016. The greatest changes in AI hiring rates can be seen in Chile and in Turkey (possibly due to a lower starting rate). In Slovenia, the AI hiring rate in 2020 is lower than in 2016. 

Note: LinkedIn data does not represent a randomised sample of the gainfully employed population of a country. It is based on statements by LinkedIn users and as such does not necessarily represent all gainfully employed persons in a country, even if a high proportion of those gainfully employed in many countries are LinkedIn users. The analyses presented here show the world from the perspective of LinkedIn, i.e. results are influenced by who uses LinkedIn and how. Depending on the country, this may be different and is influenced by various factors such as professional, socio-economic, regional or cultural background. This indicator only shows OECD countries with 100,000 LinkedIn members or more.

AI definition: AI talent is defined here as any LinkedIn user who has explicitly listed one of the AI skills identified by LinkedIn on his/her LinkedIn profile or who has specified an AI job defined by LinkedIn in his/her curriculum vitae. Examples of the skills identified by LinkedIn as AI skills include machine learning, natural language processing, data structures, artificial intelligence, computer vision, image processing, deep learning, TensorFlow, Pandas (software) and OpenCV. Examples that are classified by LinkedIn as AI jobs include machine learning engineer, artificial intelligence engineer, computer vision engineer. The complete list of AI skills and AI jobs is the property of LinkedIn and is not publicly available.

Methodology: LinkedIn calculates the hiring rate of AI talents for every country as follows: the number of AI talents who specified both a new job as well as a new employer on their LinkedIn profiles in a month in 2020, divided by the number of all LinkedIn users in a country. Further information can be found in the methodological note of the OECD AI Policy Observatory (OECD.AI).

Continuous increase in the hiring rate of AI talents in Germany

As the indicator “Hiring rates of AI talents in selected OECD countries” clearly shows, AI talents are in strong demand: their capabilities and skills are needed for artificial intelligence applications and there are too few of them on the labour market.

This scenario raises the question as to how demand for employees with AI skills has changed in recent years. Therefore, this indicator shows the rate at which AI talents are hired in Germany. The result: over the course of time, we can see that they have been hired in greater numbers since 2017, which clarifies the strong demand for AI talents.

Note: LinkedIn data does not represent a randomised sample of the working population of a country. It is based on statements by LinkedIn users and as such does not necessarily represent all economically active persons in a country, even if a high proportion of those in many countries are LinkedIn users. The analyses presented here show the world from the perspective of LinkedIn, i.e. results are influenced by who uses LinkedIn and how. Depending on the country, this may be different and is influenced by various factors such as professional, socio-economic, regional or cultural background. In Germany, less than 40% of the working population are on LinkedIn.

AI definition: AI talent is defined here as any LinkedIn user who has explicitly listed one of the AI skills identified by LinkedIn on his/her LinkedIn profile or who has specified an AI job defined by LinkedIn in his/her curriculum vitae. Examples of the skills identified by LinkedIn as AI skills include machine learning, natural language processing, data structures, artificial intelligence, computer vision, image processing, deep learning, TensorFlow, Pandas (software) and OpenCV. Examples that are classified by LinkedIn as AI jobs include machine learning engineer, artificial intelligence engineer, computer vision engineer. The complete list of AI skills and AI jobs is the property of LinkedIn and is not publicly available.

Methodology: LinkedIn calculates the hiring rate of AI talents for every country as follows: the number of AI talents who specified a new job and a new employer on their LinkedIn profiles in the same month in 2020, divided by the number of all LinkedIn users in a country. The AI hiring rates index is calculated as a moving average over twelve months in order to smooth the curve. Further information can be found in the methodological note of the OECD AI Policy Observatory (OECD.AI).

AI skills: Germany ranks in 2nd place internationally

How widespread are AI skills in Germany compared with other OECD countries? The indicator “Relative penetration of AI skills in OECD countries” – developed by LinkedIn and used by the OECD.AI Policy Observatory – shows that LinkedIn users in Germany specify AI skills 1.58 times as frequently as the OECD average. Compared with other OECD countries, Germany is therefore in second place behind the USA and ahead of Israel, Canada, South Korea, Japan, the United Kingdom and France. This shows that Germany is comparatively well positioned internationally with regard to AI skills, but has come catching up to do compared with the USA.

Note: LinkedIn data does not represent a randomised sample of the working population of a country. LinkedIn data is based on statements by LinkedIn users and as such does not necessarily represent all economically active persons in a country, even if a high proportion of those in many countries are LinkedIn users. The analyses presented here show the world from the perspective of LinkedIn, which is influenced by how LinkedIn users make use of LinkedIn. This can depend greatly on the professional, socio-economic, regional or cultural background as well as on the availability and accessibility of the LinkedIn website.

AI definition: The definition of AI skills presented here covers a list of skills that were identified by LinkedIn as AI skills. This list includes machine learning, natural language processing, data structures, artificial intelligence, computer vision, image processing, deep learning, TensorFlow, Pandas (software) and OpenCV. The complete list of AI skills is the property of LinkedIn and is not publicly available. For more information about the LinkedIn Skill Group Classification, see also: World Bank Group, LinkedIn (2018), Data Insights: Jobs, Skills and Migration Trends Methodology & Validation Results, Appendix F.

Methodology: The indicator “Relative penetration of AI skills” is based on the Skills Genome Index developed by LinkedIn, which records the top 50 skills that are “both unique and representative” for a job title and then calculates the proportion of skills classified by LinkedIn as AI skills for this job title.

The penetration with AI skills in a country is defined as the average proportion that AI skills represent in the Skills Genomes of all job titles in this country. Since the list of job titles can vary from country to country, the indicator is not directly comparable across all countries. To enable an international comparison of the indicators, the relative penetration with AI skills is defined as the relationship between the penetration with AI skills in one country and the average penetration with AI skills in all countries. In this context, only job titles that occur in all countries are included. This indicator only shows countries with more than 100,000 LinkedIn users. It can be assumed that digital skills are relatively well represented on LinkedIn in the developed economies. Further information can be found in the methodological note of the OECD AI Policy Observatory (OECD.AI).

About LinkedIn

The professional networking service LinkedIn connects employees with employers and provides a platform for exchanging information, finding jobs, accessing further training opportunities and networking. All LinkedIn members have the option of listing their skills on their profiles. The member profiles can be matched with job advertisements that companies publish on the platform. There are currently around 740 million LinkedIn members worldwide and the platform advertises more than eleven million vacancies.

All LinkedIn members have the option of listing their skills on their profiles. The skills listed by members are self-evaluations although they can be confirmed by members in their personal network. There are currently more than 35,000 different, standardized skills that have been classified by LinkedIn. These are continuously updated with the help of algorithms that record the newly added skills of members. LinkedIn groups the skills specified by members into a taxonomy of 249 Skill Group Classifications, which are statistically evaluated in anonymised form for this data record.

The data on this career network does not cover the different areas of the German labour market to the same extent. Some sectors and regions are more strongly represented than others. In particular, the economic sectors “Industry”, “freelance, scientific, technical services” and “information and communication” are well represented. In contrast to official statistics, participation in the LinkedIn network and information shared by members is entirely voluntary.

The Policy Lab Digital Work and Society and the AI Observatory analyse work in their societal contexts. This also applies to a comprehensive understanding of AI technologies. To what extent is social diversity represented in AI research? What level of acceptance is there among the general public for the use of AI outside the workplace – for example, in government organisations?

Too few women in AI research in Germany

Why is diversity important in the development of AI applications? Initial investigations support the hypothesis that diversity in AI development teams leads to a greater variety of perspectives and consequently to more diverse and more inclusive AI systems (Stathoulopoulos, K., J. Mateos-Garcia (2019)).

The indicator “gender diversity in AI research” developed by British innovation foundation Nesta shows whether women are over- (positive values) or under-represented (negative values) in AI research in the respective country. The negative value for Germany indicates that women in AI research tend to be under-represented in comparison to other countries.

AI definition: To identify studies with an AI relevance on arXiv, Nesta developed its own information retrieval system rather than using the arXiv categories (cs.AI, cs.NE). The information retrieval system developed is based on an enhanced query method and a concept of machine learning that projects words into a vector space. In the vector space, it is possible to measure the similarity between words. This approach makes it possible to use synonyms and related terms – in addition to a term that is used to start the search. This improves the completeness of the vocabulary in the query. This method identified 2,250 search terms with an AI relevance, which were then used to find studies with an AI relevance on ArXiv. You can find additional information in the Nesta study.

Methodology: The analysis on which the indicator is based was conducted by the British innovation foundation Nesta and published in the study “Gender Diversity in AI Research” together with other results about the topic. The data on which the analysis is based comes from the arXiv document server for preprints, which is widely used in AI research. For the analysis, all available studies were collected via the arXiv application programming interface in March 2019. Studies without a summary and with fewer than 300 characters or from which it was possible to detect that they had been withdrawn from arXiv were removed from the data record. Roughly 87% of these studies were also supplemented with the Microsoft Academic Graph database, which contains a further 140 million studies. Studies were allocated to countries primarily using the Google Places API. The genders of authors were allocated using the Gender API. The relative representation of women represented by a z-test, which compares the proportion of women authors of AI publications to the proportion of women authors in all publications. You can find additional information in the Nesta study.

Clear rejection of AI use in courts of law and in political decision-making

How do people in Germany feel about the use of AI in different business areas? This indicator clearly shows that there are different assessments of AI solutions across different areas of application.

The highest level of approval for the use of AI relates to industrial production while the highest degree of opposition to AI applies to its use in courts of law and in political decision-making. It can also be established that opposition to the use of AI tend to be higher in state institutions than in private companies. Generally speaking, men are more optimistic than women. Those aged 18-39 years as well as pensioners above the age of 70 favour the more widespread use of AI, more than 40-69-year-olds. These results suggest that the risk posed by AI applications is viewed differently across different areas of society. 

AI definition: The respondents of this survey were not provided with a definition of AI. Therefore, the answers given by the respondents are based on their current perception of AI.

Methodology: The data underpinning the indicator is based on a survey of around 10,705 persons over 18 years of age who use the Internet at least occasionally. The survey is conducted initially every four weeks by the Institut forsa Politik & Sozialforschung GmbH as part of the project “Opinion Monitor Artificial Intelligence (MeMo:KI)” initiated by the Centre for Advanced Internet Studies and the University of Düsseldorf. The project has been funded until March 2021 by the Ministry of Culture and Science of the State of North-Rhine-Westphalia. Since April 2021 the project is funded by Mercator Foundation.

The precise question that was presented to the respondents is as follows: “In society, there are different points of view regarding the use of artificial intelligence in different areas. Some people are in favour of it and some against. Below, you can see a list of different areas in which artificial intelligence could be used in the future. Are you more in favour of or against the user of artificial intelligence...” The possible answers are on a scale from 1 (completely against) to 5 (completely in favour). In total, answers from 4.005 respondents are shown from a random sample weighted for the gender, age and region (federal state) characteristics. The data was then aggregated, and an average was calculated for the period from January until April 2021 (week 1, 5, 9, 13; N=4.005 respondents). You can find additional information about the MeMo:KI - CAIS NRW project and the Detailed Methodology Overview in the corresponding links.

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