Prof. Dr. Thorsten Jungmann (last updated 2026-11-03)
Relates to FTS-05 Future trends in technology and society and how to evaluate sources
Task
Do this exercise here in the session, directly after FTS-05, chapter 2. You apply the four tools from that chapter to short cases. The publications and figures are real, and I use most of them in FTS-05, chapter 4; the students in tasks 3 and 4 are made up. Work through the four tasks one after the other; the solution is below each task.
1 Types of sources
Place each of these four publications in the table in FTS-05, 2.2: Is it scientific literature or grey literature, and if it is grey literature, in which tier? Give a reason.
a) An article in a journal of the Institute of Electrical and Electronics Engineers (IEEE) on migrating control software from one standard to another (Ashiwal et al. 2025).
b) A special report in which the European Court of Auditors (ECA) audits the strategy of the European Union (EU) for microchips (ECA 2025).
c) A press release of World Semiconductor Trade Statistics (WSTS), an organization of semiconductor companies, on the global semiconductor market in 2025 (WSTS 2026).
d) A post on the online platform Medium in which Jamais Cascio proposes a framework: brittle, anxious, nonlinear, incomprehensible (BANI) (Cascio 2020).
Solution
a) Scientific literature: Published journal papers belong here (Garousi et al. 2019, p. 4). The article has been through a peer review: it states when it was received and accepted and names the editor who arranged the review (Ashiwal et al. 2025, p. 575).
b) Grey literature, first tier: Government reports belong here (Garousi et al. 2019, p. 4), and this report is the result of an audit of EU policy (ECA 2025, back cover).
c) Grey literature, second tier: The model does not mention press releases; as in FTS-05, 2.2, I put them next to annual reports.
d) Grey literature, third tier: Garousi et al. (2019, p. 4) put blogs here, and this post is closest to them. Yet a lower tier does not make a publication useless: this post is where Cascio proposes BANI, which is why FTS-01, 5.5 cites it.
The assignment is mine, as it is in the lesson. Garousi et al. (2019, p. 3) describe a range rather than sharp categories.
2 Interests
Here are three publications and what they say about themselves. For each one: Who wrote it, who paid for it, as far as it says so, and who could benefit if it is well received? Then rewrite the sentence below the three publications so that it says who is speaking.
a) World Robotics 2025: industrial robots reports that 542 076 industrial robots were installed worldwide in 2024 (Müller 2025, p. 13). It comes from the statistical department of the International Federation of Robotics (IFR), and its statistics rest on reports by robot suppliers and national robotics associations (ibid., imprint). The imprint, the page with the publication details, adds that a company sponsors the cover and the editorial (ibid., imprint). On its website, the IFR names where its members come from: the robotics industry, industry associations and research institutes. One of its aims is ‘to promote and strengthen the robotics industry worldwide’ (IFR 2026).
b) State and Trends of Carbon Pricing 2026 reports that 87 direct carbon pricing instruments covered 29 % of global greenhouse gas emissions on 1 April 2026 (World Bank 2026, pp. 5, 13). According to its imprint, the staff of the World Bank wrote it, with contributions from outside (ibid., p. i). According to its acknowledgements, it was developed as part of a programme under the Partnership for Market Implementation (ibid., p. ii). Its foreword says: ‘At the World Bank Group, our objective is to support both scale and integrity for carbon pricing and carbon markets.’ (ibid., p. 3)
c) The article from task 1 has five authors. One of them works at the corporate research centre of a company and at Johannes Kepler University Linz; of the other four, two work at this university and two at Universitat Jaume I in Spain. According to the first page, a research project of Universitat Jaume I supported the work (Ashiwal et al. 2025, p. 575).
The sentence to rewrite: ‘Studies show that 542 076 industrial robots were installed worldwide in 2024.’
Solution
a) Who wrote it: the statistical department of the IFR, with figures from robot suppliers and national robotics associations (Müller 2025, imprint). Who paid: The imprint names one sponsor, a company, for the cover and the editorial (ibid., imprint). Who could benefit: the robotics industry, which the IFR itself wants to promote and strengthen (IFR 2026). So this is a publication funded by industry (FTS-05, 2.3).
b) Who wrote it: the staff of the World Bank (World Bank 2026, p. i). Who paid: The report names the programme under which it was developed (ibid., p. ii), but you do not learn from these details who paid for it; this, too, is a finding. Who could benefit, a possible answer: The World Bank itself wants to support carbon pricing (ibid., p. 3), and a report that shows how far it has spread suits this objective. An interest need not be the interest of a company.
c) Who wrote it: researchers at two universities, one of whom also works at a company (Ashiwal et al. 2025, p. 575). Who paid: a research project of a university (ibid., p. 575). Who could benefit: The first page does not tell you whether the company benefits from the result; you would now ask further. By the definition in FTS-05, 2.3, a publication written by employees of companies counts as funded by industry; here, that applies to one of five authors. The article has been through a peer review, and still one of its authors works for a company: this is why the type of source alone is not enough (FTS-05, 2.2).
In all three cases, an interest does not make a statement wrong. It is a reason to ask further: Do the data back up the conclusions (Garousi et al. 2019, p. 19)?
The sentence, a possible answer: ‘According to the International Federation of Robotics, whose statistics rest on reports by robot suppliers and national robotics associations (Müller 2025, imprint), 542 076 industrial robots were installed worldwide in 2024 (ibid., p. 13).’ ‘Studies show …’ hides who is speaking.
3 What was examined
Three students draw conclusions from figures. For each case: What exactly was measured, compared with what and in which case? Does the conclusion hold? If it does not, how would you put it?
a) A student writes: ‘The sources contradict each other: according to Eurostat, the figure for artificial intelligence (AI) is 19.95 %; according to the World Economic Forum (WEF), it is 86 %.’ These are the two figures: Of the enterprises in the EU with at least ten employees, 19.95 % used at least one AI technology in 2025 (Eurostat 2025, p. 1). In a survey of over 1 000 employers in 55 economies, 86 % expect AI and information processing to transform their business by 2030 (WEF 2025).
b) On a poster, a student writes: ‘More than half of manufacturers let their customers take part in product design (Patalas-Maliszewska et al. 2025, p. 23).’ This is what the article says: The survey ran from January to August 2023 and covered 153 manufacturing enterprises in the automotive sector in Poland, of which 117 were small and medium-sized enterprises (SMEs) (ibid., p. 22). Among these SMEs, 55.56 % let customers take part in designing the product (ibid., p. 23).
c) A student writes: ‘The world has never been as uncertain as in the third quarter of 2025: the World Uncertainty Index reached its highest value so far, 106 862.’ This is what the data page says: The index measures uncertainty by how often the word ‘uncertainty’ occurs in the quarterly country reports of the Economist Intelligence Unit, and the series begins in 1990 (FRED 2026).
Solution
a) The conclusion does not hold: the two figures measure different things. Eurostat reports use in 2025; the WEF reports an expectation up to 2030. Eurostat counts enterprises in the EU with at least ten employees; the WEF asks employers in 55 economies. A possible answer: ‘Of the enterprises in the EU with at least ten employees, 19.95 % used AI in 2025 (Eurostat 2025, p. 1), while 86 % of the employers surveyed by the WEF expect AI and information processing to transform their business by 2030 (WEF 2025).’
b) The conclusion goes beyond the data. The figure applies to SMEs from one sector in one country, not to manufacturers in general. A possible answer: ‘In a survey from 2023 of 117 SMEs in the automotive sector in Poland, 55.56 % let customers take part in designing the product (Patalas-Maliszewska et al. 2025, pp. 22–23).’
c) The conclusion goes beyond what the index captures. Validity means that a method captures what it claims to capture (Jungmann 2025, p. 18). The index captures how often a word occurs in certain reports. Uncertainty itself cannot be observed, and there is no perfect measure of it, only proxies, that is, indirect measures such as the volatility of stock markets or how often the news mentions the word (Bloom 2013, p. 3). And ‘never’ goes further than a series that begins in 1990. A possible answer: ‘The World Uncertainty Index, which counts how often the word “uncertainty” occurs in quarterly country reports, reached its highest value since 1990 in the third quarter of 2025 (FRED 2026).’
4 The same question twice
a) Four students each want to put their question to their AI service twice and compare the two answers. Who does it in a way that allows a comparison? What is wrong with the others?
- Student A asks the question, reads the answer and then types ‘Are you sure?’ in the same chat.
- Student B opens a new chat with the same service, model and mode and asks the question again, in shorter words.
- Student C opens a new chat with the same service and model and asks the question again, word for word, but in a thinking mode instead of an instant mode.
- Student D opens a new chat with the same service, model and mode and asks the question again, word for word.
b) In FTS-05, 2.5, you have seen passages from two answers to our example question, ‘Does hydrogen make steel production climate-neutral?’ Both answers also list what is left even with ‘green hydrogen’; the first one speaks of carbon dioxide (CO₂). Compare the two lists: What do both answers name? What does only one of them name? What do you conclude, and what do you do next?
Claude, first query
‘Carbon in the product: steel is an iron–carbon alloy, so some carbon has to be added, often from fossil sources. […] Graphite electrodes in the arc furnace burn off and release CO₂. […] Lime and fluxes: making quicklime from limestone releases process CO₂. […] Upstream and downstream steps: mining, pelletising, transport, reheating and rolling (often still with natural gas). […] Building the plants: electrolysers, wind turbines and solar panels carry embodied emissions.’ (Claude, Claude app for macOS, Claude Opus 5.5 with effort xhigh, queried 2026-10-16) – AI output, quoted as an example – not evidence.
Claude, second query
‘Carbon added to the steel and the melt, unless it comes from non-fossil sources […] Lime production and the consumption of graphite electrodes […] Natural gas used for reheating and rolling, unless these steps are electrified […] Ore mining, pelletising and transport […] Hydrogen leaks, because hydrogen acts as an indirect greenhouse gas’ (Claude, Claude app for macOS, Claude Opus 5.5 with effort xhigh, queried 2026-11-02) – AI output, quoted as an example – not evidence.
Solution
a) Student D. A reliable study leads to comparable results when it is repeated under the same conditions (Jungmann 2025, p. 19), and in FTS-05, 2.5 that means word for word, with the same service and the same model and mode, in a new chat. Student A does not repeat the question at all: ‘Are you sure?’ is a different question, and it comes in the same chat. Student B changes the wording, and student C changes the mode, so you could not tell where a difference comes from.
b) Both answers name: carbon in the steel, graphite electrodes, lime, mining, pelletizing, transport and natural gas for reheating and rolling. Only the first names: fluxes and building the plants. Only the second names: carbon added to the melt and hydrogen leaks.
What you conclude, a possible answer: The core stays the same, and the details differ. This tells you something about reliability, not about truth: what both answers name can still be wrong, and what only one names is not wrong for that reason. Neither list names a source.
What you do next: You check the passages against scientific sources. On a poster, you quote what you examine from both answers, each with its long reference and the note, and in the column for the AI answer, you report what the comparison has shown.
Bibliography
- ASHIWAL, Virendra, MIGUEL-ESCRIG, Oscar, WIESMAYR, Bianca, ZOITL, Alois and ROMERO-PÉREZ, Julio-Ariel, 2025. Identification and evaluation of pitfalls in the migration from IEC 61131-3 to IEC 61499: a review. IEEE Open Journal of the Industrial Electronics Society [online]. 6, 575–590. Available from: https://doi.org/10.1109/OJIES.2025.3558685 [viewed 2026-11-03].
- BLOOM, Nicholas, 2013. Fluctuations in uncertainty [online]. NBER Working Paper 19714. Cambridge, MA: National Bureau of Economic Research. Available from: https://doi.org/10.3386/w19714 [viewed 2026-11-03].
- CASCIO, Jamais, 2020. Facing the age of chaos [online]. 29 April 2020. Medium. Available from: https://medium.com/@cascio/facing-the-age-of-chaos-b00687b1f51d [viewed 2026-11-03].
- ECA, 2025. Special report 12/2025: the EU’s strategy for microchips: reasonable progress in its implementation but the Chips Act is very unlikely to be sufficient to reach the overly ambitious Digital Decade target [online]. Luxembourg: European Court of Auditors, Publications Office of the European Union. Available from: https://www.eca.europa.eu/ECAPublications/SR-2025-12/SR-2025-12_EN.pdf [viewed 2026-11-03].
- EUROSTAT, 2025. Use of artificial intelligence in enterprises [online]. Statistics Explained. Data extracted in December 2025. Available from: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises [viewed 2026-11-03].
- FRED, 2026. World Uncertainty Index: global: GDP weighted average (WUIGLOBALWEIGHTAVG) [online]. Data by Hites Ahir, Nicholas Bloom and Davide Furceri. Federal Reserve Bank of St. Louis. Last updated 15 October 2026. Available from: https://fred.stlouisfed.org/data/WUIGLOBALWEIGHTAVG [viewed 2026-11-03].
- GAROUSI, Vahid, FELDERER, Michael and MÄNTYLÄ, Mika V., 2019. Guidelines for including grey literature and conducting multivocal literature reviews in software engineering. Information and Software Technology [online]. 106, 101–121. Pages cited from the pre-print of the accepted paper. Available from: https://arxiv.org/abs/1707.02553 [viewed 2026-11-03].
- IFR, 2026. About IFR [online]. International Federation of Robotics. Available from: https://ifr.org/association [viewed 2026-11-03].
- JUNGMANN, Thorsten, 2025. Abschlussarbeiten aus Prüfersicht: Bachelor-, Master- oder Doktorarbeit schreiben und selbst bewerten – Leitfaden zur Bestnote [Final theses from an examiner’s perspective]. Herne: Prof. Dr. Thorsten Jungmann. ISBN 978-3-911872-02-7.
- MÜLLER, Christopher, 2025. World Robotics 2025: industrial robots. Executive summary [online]. Frankfurt am Main: IFR Statistical Department, VDMA Services GmbH. ISBN 978-3-8163-0771-6. Available from: https://ifr.org/img/worldrobotics/Executive_Summary_WR_2025_Industrial_Robots.pdf [viewed 2026-11-03].
- PATALAS-MALISZEWSKA, J., KOWALCZEWSKA, K. and PAJAK, G., 2025. Mass customization in practice: strategic implementation and insights from Polish small and medium sized enterprises. Advances in Production Engineering & Management [online]. 20(1), 18–28. Available from: https://doi.org/10.14743/apem2025.1.524 [viewed 2026-11-03].
- WEF, 2025. The future of jobs report 2025 [online]. Geneva: World Economic Forum. Available from: https://www.weforum.org/publications/the-future-of-jobs-report-2025/digest/ [viewed 2026-11-03].
- WORLD BANK, 2026. State and Trends of Carbon Pricing 2026 [online]. Washington, DC: World Bank. Available from: https://doi.org/10.1596/978-1-4648-2348-0 [viewed 2026-11-03].
- WSTS, 2026. Global semiconductor market grows 26% in 2025 to $796 billion [online]. Press release. San Jose, California: World Semiconductor Trade Statistics. 6 March 2026. Available from: https://www.wsts.org/esraCMS/extension/media/f/WST/7495/WSTS-Q4-Release-2025_-_06-Mar-2026.pdf [viewed 2026-11-03].
Overview of tools used
In creating this script, AI-supported software tools were used to generate and revise text and images according to my specifications:
| Product name | Access source | Software functions used | Scope of use |
|---|---|---|---|
| Perplexity | https://www.perplexity.ai | Search | Research |
| Gemini | https://gemini.google.com | Search | Research |
| Connected Papers | https://www.connectedpapers.com | Graphs of related papers | Research |
| Claude | https://claude.ai | Claude Opus and Claude Fable | Consistency checking, corrections, text revision and translation |
| Claude | Claude app for macOS | Claude Opus 5.5 with effort xhigh | Answers to the example question, examined in task 4 |