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. Blackwell, Oxford, UK. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From Data Mining to Knowledge Discovery in Databases. AI Magazine, 17(3), 37-54. Grüne-Yanoff, T. (2012). Paradoxes of Rational Choice Theory. In: Roeser S., Hillerbrand R., Sandin P., Peterson M. (eds) Handbook of Risk Theory. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1433-5_19 Gudonavičius, L., & Savanevičiene, A. (2018). Knowledge Organizations: Rational and Creative Thinking in Strategic Decision Making. Retrieved from https://www.researchgate.net/publication/228466245

REFERENCES Clifford, C. (2018). Elon Musk: ‘Mark my words — A.I. is far more dangerous than nukes’ . CNBC International , available at: https://www.cnbc.com/2018/03/13/elon-musk-at-sxsw-a-i-is-more-dangerous-than-nuclear-weapons.html , accessed on 05 October 2019. Cuthbertson, A. (2019). Google ‘achieves quantum supremacy’. INDEPENDENT , available at: https://www.independent.co.uk/life-style/gadgets-and-tech/news/google-quantum-supremacy-computers-nasa-a9116371.html , accessed on 05 October 2019. Dickson, B. (2017). What is Narrow, General and Super

volumes grow, so do new algorithms to process and ana- lyze unstructured data. Artificial Intelligence (AI) is one of the domains that can help open this treasure box fur- ther to better understand consumer decision-making. In a GfK research project, we tested how we can learn con- sumer preferences and predict choices from publicly avail- able social media and review data which are related to sales data. The common AI tool “Word Embeddings” has shown to be a powerful way to analyze the words that people use. It enabled us to reveal consumers’ preferred brands

Odkazy [1] Výzkum potenciálu rozvoje umělé inteligence v České republice. Souhrnná zpráva. Studie vypracovaná pro Úřad vlády ČR Technologickým centrem AV ČR a ČVUT v Praze. Úřad vlády ČR (2018). https://www.vlada.cz/assets/evropske-zalezitosti/aktualne/AI-souhrnnazprava-2018.pdf [2] Inciativa Průmysl 4.0. Ministerstvo průmyslu a obchodu (2016). https://www.mpo.cz/cz/prumysl/zpracovatelsky-prumysl/prumysl-4-0-ma-v-cesku-sve-misto--176055/ [3] Arntz, M., Gregory, T., Zierahn, U.: The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis. OECD

in ERGO

Odkazy [1] Výzkum potenciálu rozvoje umělé inteligence v České republice. Souhrnná zpráva. Studie vypracovaná pro Úřad vlády ČR Technologickým centrem AV ČR a ČVUT v Praze. Úřad vlády ČR (2018). https://www.vlada.cz/assets/evropske-zalezitosti/aktualne/AI-souhrnna-zprava-2018.pdf [2] Výzkum potenciálu rozvoje umělé inteligence v České republice. Výzkumné, technologické a podnikové zázemí v ČR. Analýza pozice České republiky v oblasti technologického rozvoje umělé inteligence. Studie vypracovaná pro Úřad vlády ČR Technologickým centrem AV ČR a ČVUT v Praze. Úřad

in ERGO

situations occur. While a human driver has to spontaneously react in a The Thorny Challenge of Making Moral Machines: Ethical Dilemmas with Self-Driving Cars Edmond Awad, Jean-François Bonnefon, Azim Shariff and Iyad Rahwan KE Y WORDS Ethics, Decision Making, AI, Autonomous Vehicles, Moral Machines THE AUTHORS Edmond Awad The Media Lab, Institute for Data, Systems and Society, Massachusetts Institute of Technology, Cambridge, MA, USA awad@mit.edu Jean-François Bonnefon Toulouse School of Economics (TSM-R, CNRS), Université Toulouse-1 Capitole, Toulouse

Mind Model for Multimodal Communicative Creatures and Humanoids. International Journal of Applied Artificial Intelligence . 13:(4-5): 519-538. Thórisson, K. R., Benko, H., Abramov D., Arnold, A., Maskey, S., Vaseekaran A. 2004. Constructionist Design Methodology for Interactive Intelligences. AI Magazine . 25(4): 77-90. Thórisson, K. R. 2009. From Constructionist to Constructivist A. I. Keynote, Technical Report, FS-09-01, AAAI press, Menlo Park, Calif. Wang, P. 1995. Non-Axiomatic Reasoning System: Exploring the Essence of Intelligence . Ph.D. diss., Dept. of

update on North American boar stud practices. Theriogenology 70: 1202-1208. 6. Feitsma, H. (2009). Artificial insemination in pigs, research and developments in The Netherlands, a review. Acta Scientiae Veterinariae 37 (Suppl. 1): 61-71. 7. Broekhuijse, M.L.W.J., Feitsma, H., Gadella, B.M. (2011). Field data analysis of boar semen quality. Reprod Domest Anim 46 (Suppl. 2): 59-63. 8. Vyt, P., Maes, D., Rijsselaere, T., Dewulf, J., De Kruif, A., Van Soom, A. (2007). Semen handling in porcine AI centers: the Belgian situation. Vlaams Diegeneeskundig Tijdschrift 76: 195

lactating dairy cows. Reprod. Domest. Anim., 50: 497-504. Colazo M.G., Kastelic J.P., Whittaker P.R., Gavaga Q.A., Wilde R., Mapletoft R.J. (2004). Fertility in beef cattle givenanew or previously used CIDRinsert and estradiol, with or without progesterone. Anim. Reprod. Sci., 81: 25-34. Colazo M.G., Dourey A., Rajamahendran R., Ambrose D.J. (2013). Progesterone supplementation before timed AIincreased ovulation synchrony and pregnancy per AI, and supplementation after timed AIreduced pregnancy losses in lactating dairy cows. Theriogenology, 79: 833-841. De Rensis F

Abstract

Whatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms that process this data.

AI has the potential to make our life easier, but this convenience might come at a price which we have to pay such as biases directly built-in to the algorithms we use, data privacy issues or failed AI projects in business practice. But without testing, failing, and learning from our failures, there