• Abstract

    The broad acceptance and incorporation of artificial intelligence (AI) have significantly influenced a country's economy and human life. AI is used in industries, government, and even academic institutions to make decisions that have a direct and potential impact on lives. The integration of AI technology is a necessary step in developing intelligent manufacturing and the future smart factory. Improve diagnostic accuracy and screening time savings on business challenges are possible with artificial intelligence. This research helps to identify the superior AI technologies used in various areas, comprehend AI technologies and how they are applied, and determine AI opportunities and challenges. The deployment of AI in different sectors affects both producers and consumers. To reduce resistance of employees due to fear of technology, employers must make them aware of the usage of AI applications. One of the data challenges is a lack of quality of input data. The sharing of data and lack of trust are ethical challenges. There are challenges to the adoption of artificial intelligence all over the globe. Artificial intelligence-based start-ups face challenges due to the need for more suitable infrastructure. The increasing use of artificial intelligence can potentially change many aspects of human existence.

  • References

    1. Abarca-Alvarez FJ, Campos-Sanchez FS, Reinoso-Bellido R (2018) Demographic and Dwelling Models by Artificial Intelligence: Urban Renewal Opportunities in Spanish Coast. International Journal of Sustainable Development and Planning, 13:941–953. https://doi.org/10.2495/SDP-V13-N7-941-953.
    2. Akgun S, Greenhow C (2021) Artificial Intelligence in Education: Addressing Ethical Challenges in K-12 Settings. AI and Ethics 1–10. https://doi.org/10.1007/S43681-021-00096-7.
    3. Alzoubi I, Delavar M, Mirzaei F, Nadjar-Arrabi B (2017) Integrating Artificial Neural Network and Imperialist Competitive Algorithm (ICA) to Predict the Energy Consumption for Land Leveling. International Journal of Energy Sector Management 11: 522–540 https://doi.org/10.1108/IJESM-01-2017-0003.
    4. Anjomshoae S, Calvaresi D, Najjar A, Främling K (2019) Explainable Agents and Robots: Results from a Systematic Literature Review. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems 2:1078–1088.
    5. Arlitsch K, Newell B (2017) Thriving in the Age of Accelerations: A Brief Look at the Societal Effects of Artificial Intelligence and the Opportunities for Libraries. Journal of Library Administration 57:789–798. https://doi.org/10.1080/01930826.2017.1362912.
    6. Asatiani A, Malo P, Nagbøl P, Penttinen E, Rinta-Kahila T, Salovaara A (2020) Challenges of Explaining the Behavior of Black-Box AI Systems. MIS Quarterly Executive 19(4). https://aisel.aisnet.org/misqe/vol19/iss4/7.
    7. Azizpour S, Smith H, Hartman K (2018) Digital Image Analysis in Breast Pathology-from Image Processing Techniques to Artificial Intelligence. Translational Research: The Journal of Laboratory and Clinical Medicine 194:19–35. https://doi.org/10.1016/j.trsl.2017.10.010.
    8. Barocas S, Selbst AD (2018) Big Data’s Disparate Impact. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2477899.
    9. Beregi JP, Zins M, Masson JP, Cart P, Bartoli JM, Silberman B, Boudghene F, Meder JF (2018). Radiology and Artificial Intelligence: An Opportunity for our Specialty. Diagnostic and Interventional Imaging 99:677–678. https://doi.org/10.1016/J.DIII.2018.11.002.
    10. Burrell J. (2016). How the machine ‘thinks’: Understanding Opacity in Machine Learning Algorithms 3. https://doi.org/10.1177/2053951715622512.
    11. Kayembe C (2019) Challenges and Opportunities for Education in the Fourth Industrial Revolution. African Journal of Public Affairs 11:79–94.
    12. Carleton RN (2016) Into the Unknown: A Review and Synthesis of Contemporary Models Involving Uncertainty. In Journal of Anxiety Disorders 39:30–43. https://doi.org/10.1016/j.janxdis.2016.02.007.
    13. Chatterjee S (2020) AI strategy of India: Policy Framework, Adoption Challenges and Actions for Government. Transforming Government: People, Process and Policy 14:757–775. https://doi.org/10.1108/TG-05-2019-0031.
    14. Chaudhri VK, Gunning D, Lane HC, Roschelle J (2013) Intelligent learning Technologies Part 2: Applications of Artificial Intelligence to Contemporary and Emerging Educational Challenges. AI Magazine 34:10–12. https://doi.org/10.1609/aimag.v34i4.2518.
    15. Dawes J (2021) An Autonomous Robot may have already killed people – here’s how the weapons could be more destabilizing than nukes. https://theconversation.com/an-autonomous-robot-may-have-already-killed-people-heres-how-the-weapons-could-be-more-destabilizing-than-nukes-168049 Accessed on October 2022.
    16. Dignum V (2021) The Role and Challenges of Education for Responsible AI. London Review of Education 19:1–11. https://doi.org/10.14324/LRE.19.1.01.
    17. Dreyer K, Allen B (2018) Artificial Intelligence in Health Care: Brave New World or Golden Opportunity? Journal of the American College of Radiology 15:655–657. https://doi.org/10.1016/j.jacr.2018.01.010.
    18. Smith G (2021) AN EPIC FAILURE: OVERSTATED AI CLAIMS IN MEDICINE. Structural Engineer 99:5-20.
    19. Hornung O, Smolnik S (2022) AI Invading the Workplace: Negative Emotions towards the Organizational Use of Personal Virtual Assistants. Electronic Markets 32:123–138. https://doi.org/10.1007/S12525-021-00493-0.
    20. Houssami N, Lee CI, Buist DSM, Tao D (2017) Artificial Intelligence for Breast Cancer Screening: Opportunity or hype? Breast 36:31–33. https://doi.org/10.1016/j.breast.2017.09.003.
    21. Jain PK, Mosier CT (2007) Artificial Intelligence in Flexible Manufacturing Systems. International Journal of Computer Integrated Manufacturing 5:378–384. https://doi.org/10.1080/09511929208944545.
    22. Jason B, Ayanna H (2020) Emerging Challenges in AI and the Need for AI ethics education. AI and Ethics 1:61–65. https://doi.org/10.1007/S43681-020-00002-7.
    23. Jobin A, Ienca M, Vayena E (2019) The global landscape of AI ethics guidelines. Nature Machine Intelligence 1:389–399. https://doi.org/10.1038/s42256-019-0088-2.
    24. Kahn CE (2017) From images to actions: Opportunities for Artificial Intelligence in Radiology. In Radiology .Radiological Society of North America Inc 285:719-725. https://doi.org/10.1148/radiol.2017171734.
    25. Keyes OS (2018) The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. 88:22-30.https://doi.org/10.1145/3274357.
    26. Khanna S, Sattar A, Hansen D (2013) Artificial Intelligence in Health - The Three Big Challenges. In Australasian Medical Journal.6:315–317. https://doi.org/10.4066/AMJ.2013.1758
    27. Kusiak A (2016) Artificial Intelligence and Operations Research In Flexible Manufacturing Systems. 25: 2–12. https://doi.org/10.1080/03155986.1987.11732024.
    28. Leskowitz E (2006) The Influence of Group Heart Rhythm on Target Subject Physiology: Case Report of a Laboratory Demonstration, and suggestions for further. Subtle Energies & Energy Medicine Journal, 18: 77–88.
    29. Li B, Hou B, Yu W, Lu X, Yang C (2017) Applications of Artificial Intelligence in Intelligent Manufacturing: a Review. In Frontiers of Information Technology and Electronic Engineering.18:86–96. https://doi.org/10.1631/FITEE.1601885.
    30. Liang TP, Robert L, Sarker S, Cheung CMK, Matt C, Trenz M, Turel O (2021) Artificial intelligence and robots in individuals’ lives: how to align technological possibilities and ethical issues. Internet Research, 31: 1–10. https://doi.org/10.1108/INTR-11-2020-0668/FULL/HTML.
    31. Liu H (2020). Application of Artificial Intelligence in Computer Network Technology in Big Data Era. 2020 Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC).5: 34–38. https://doi.org/10.1109/ICESIT53460.2021.9696498.
    32. Malhotra A, Schulte J, Patel P, Petesch P (2009) Innovation for Women’s Empowerment and Gender Equality. British Journal of Educational Technology, 49:1885–1901.
    33. Manne R, Kantheti SC (2021) Application of Artificial Intelligence in Healthcare: Chances and Challenges. Current Journal of Applied Science and Technology, 78–89. https://doi.org/10.9734/cjast/2021/v40i631320.
    34. McCraty R (2017) New Frontiers in Heart Rate Variability and Social Coherence Research: Techniques, Technologies, and Implications for Improving Group Dynamics and Outcomes. Frontiers in Public Health, 5. https://doi.org/10.3389/FPUBH.2017.00267/FULL.
    35. Mikhaylov SJ, Esteve M, Campion A (2018) Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376:21-28. https://doi.org/10.1098/RSTA.2017.0357.
    36. Morris SM (2010) Achieving collective coherence: Group effects on heart rate variability coherence and heart rhythm synchronization. Alternative Therapies. 16: 62–72.
    37. Muhuri PK, Shukla AK, Abraham A (2019a). Industry 4.0: A Bibliometric Analysis and Detailed Overview. Engineering Applications of Artificial Intelligence, 78:218–235. https://doi.org/10.1016/j.engappai.2018.11.007.
    38. Nikolic B, Ignjatic J, Suzic N, Stevanov B, Rikalovic A (2017) Predictive manufacturing systems in industry 4.0: Trends, benefits and challenges. Annals of DAAAM and Proceedings of the International DAAAM Symposium, 8:796–802. https://doi.org/10.2507/28th.daaam.proceedings.112.
    39. Olshannikova E, Ometov A, Koucheryavy Y,Olsson T (2015) Visualizing Big Data with augmented and virtual reality: challenges and research agenda. Journal of Big Data, 2:22-30. https://doi.org/10.1186/s40537-015-0031-2.
    40. Pillai R, Sivathanu B (2020) Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking, 27: 2599–2629. https://doi.org/10.1108/BIJ-04-2020-0186.
    41. Pribram KH (2013) Brain and Perception. In Brain and Perception. Psychology Press. https://doi.org/10.4324/9780203728390.
    42. Rana NP, Chatterjee S, Dwivedi YK, Akter S (2021) Understanding Dark Side of Artificial Intelligence (AI) Integrated Business Analytics: Assessing Firm’s Operational Inefficiency and Competitiveness. European Journal of Information Systems, 31: 364–387. https://doi.org/10.1080/0960085X.2021.1955628.
    43. Richards D, Dignum V (2019) Supporting and Challenging Learners through Pedagogical Agents: Addressing Ethical Issues through Designing for Values. British Journal of Educational Technology. 50: 2885–2901. https://doi.org/10.1111/BJET.12863.
    44. Rieder G (2018) Big Data: Or, The Vision That Would Not Fade. July, 105–110.
    45. Robbins S (2019) AI and the path to envelopment: knowledge as a first step towards the responsible regulation and use of AI-powered machines. AI & SOCIETY 2019. 35:391–400. https://doi.org/10.1007/S00146-019-00891-1.
    46. Rubik B, Jabs H (2018) Artificial Intelligence and the Human Biofield: New Opportunities and Challenges. Cosmos and History, 14:153–162.
    47. Schwartz GE, Russek LG (1997) Dynamical Energy Systems and Modern Physics: Fostering the Science and Spirit of Complementary and Alternative Medicine. Alternative Therapies in Health and Medicine, 3:46–56. https://europepmc.org/article/med/9141291.
    48. Selwyn N (2020) Re-imagining ‘Learning Analytics’ … a case for starting again? Internet and Higher Education, 46:78-99 https://doi.org/10.1016/j.iheduc.2020.100745. Serholt S, Barendregt W, Vasalou A, Alves-Oliveira P, Jones A, Petisca S, Paiva A (2017) The case of classroom robots: Teachers’ Deliberations on the Ethical Tensions. AI and Society, 32:613–631. https://doi.org/10.1007/s00146-016-0667-2.
    49. Shneiderman B (2020) Bridging the gap between ethics and practice: Guidelines for reliable, safe, and trustworthy human-centered AI systems. ACM Transactions on Interactive Intelligent Systems, 10. https://doi.org/10.1145/3419764.
    50. Solos WK, Leonard J (2022) On the Impact of Artificial Intelligence on Economy. Science Insights, 41:551–560. https://doi.org/10.15354/SI.22.RE066.
    51. Spanaki K, Gürgüç Z, Adams R, Mulligan C (2018) Data supply chain (DSC): Research Synthesis and Future Directions. Taylor & Francis, 56:4447–4466. https://doi.org/10.1080/00207543.2017.1399222.
    52. Stephen ED (2019) The HeartMath coherence model: Implications and Challenges for Artificial Intelligence and Robotics. AI and Society, 34:899–905. https://doi.org/10.1007/s00146-018-0834-8.
    53. Tarafdar M, Beath C (2020) Using AI to Enhance Business Operations. In How AI Is Transforming the Organization. https://doi.org/10.7551/mitpress/12588.003.0015.
    54. Thesmar D, Sraer D, Pinheiro L, Dadson N, Veliche R, Greenberg P (2019) Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges. Pharmaco Economics. https://doi.org/10.1007/s40273-019-00777-6.
    55. Thrall JH, Li X, Li Q, Cruz C, Do S, Dreyer K, Brink J (2018) Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. Journal of the American College of Radiology, 15:504–508. https://doi.org/10.1016/j.jacr.2017.12.026.
    56. Vincent-Lancrin S, Vlies R (2020) Trustworthy artificial intelligence (AI) in education : Promises and challenges. OECD Education Working Papers No. 218.
    57. Von-Eschenbach WJ (2021) Transparency and the Black Box Problem: Why We Do Not Trust AI. Philosophy and Technology. 34:1607–1622. https://doi.org/10.1007/S13347-021-00477-0.
    58. Zachary-Arnold-Helen-Toner A (2021) AI Accidents: An Emerging Threat What Could Happen and What to Do CSET Policy Brief.
    59. Zandi D, Reis A, Vayena E, Goodman K (2019) New ethical challenges of digital technologies, machine learning and artificial intelligence in public health: A call for papers. In Bulletin of the World Health Organization 97:2-16. https://doi.org/10.2471/BLT.18.227686.
    60. Zheng Y, Wu W, Chen Y, Qu H, Ni LM (2016) Visual Analytics in Urban Computing: An Overview. IEEE Transactions on Big Data, 2:276–296. https://doi.org/10.1109/tbdata.2016.2586447.
    61. Zhong RY, Xu X, Klotz E, Newman ST (2017) Intelligent Manufacturing in the Context of Industry 4.0: A Review. Engineering, 3:616–630. https://doi.org/10.1016/J.ENG.2017.05.015.

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Prasad Babu, P., & Vasumathi, A. (2023). Contemporary issues in applying AI applications: challenges and opportunities. Multidisciplinary Reviews, 6(1), 2023010. https://doi.org/10.31893/multirev.2023010
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