IDEAS home Printed from https://ideas.repec.org/a/vra/journl/v11y2022i2p172-183.html
   My bibliography  Save this article

Artificial Intelligence System Problems and Opportunities to Solve Them with Design Patterns

Author

Listed:
  • Mariya Armyanova

    (University of Economics - Varna, Varna, Bulgaria)

  • Yanka Aleksandrova

    (University of Economics - Varna, Varna, Bulgaria)

Abstract

Artificial intelligence (AI) is entering almost every sphere of modern life. Its influence cannot be ignored and it permeates almost all modern systems. The requirements for the development of such systems are many, he must not only know the capabilities of AI, but also be able to create a complete system that meets certain quality requirements. Some design patterns are provided to help AI developers. Common development practices at the architecture and project level can be encapsulated as patterns to reuse and bring the expertise in this relatively new technology to all developers. For some of the problems discussed, design patterns can offer an effective solution and thus support the overall development process. The research goal is to explore common problems in AI systems and patterns that can offer a solution.

Suggested Citation

  • Mariya Armyanova & Yanka Aleksandrova, 2022. "Artificial Intelligence System Problems and Opportunities to Solve Them with Design Patterns," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 11(2), pages 172-183, August.
    • Handle: RePEc:vra:journl:v:11:y:2022:i:2:p:172-183
    as

    Download full text from publisher

    File URL: http://su-varna.org/journal/IJUSV-ESS/2022.11.2/172-183.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Snezhana Sulova, 2019. "The Usage of Data Lake for Business Intelligence Data Analysis," Conferences of the department Informatics, Publishing house Science and Economics Varna, issue 1, pages 135-144.
    2. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    3. Pavel Petrov & Snezhana Sulova & Mihail Radev & Yanka Aleksandrova & Miglena Stoyanova & Liliya Mileva & Plamen Yankov, 2020. "Digitalization of business processes in construction and logistics," Monographic library "Knowledge and business" Varna, Publishing house "Knowledge and business" Varna, number 8, June.
    4. Grewal, Dhruv & Kroschke, Mirja & Mende, Martin & Roggeveen, Anne L. & Scott, Maura L., 2020. "Frontline Cyborgs at Your Service: How Human Enhancement Technologies Affect Customer Experiences in Retail, Sales, and Service Settings," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 9-25.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    2. Zhang, Weidong & Zuo, Na & He, Wu & Li, Songtao & Yu, Lu, 2021. "Factors influencing the use of artificial intelligence in government: Evidence from China," Technology in Society, Elsevier, vol. 66(C).
    3. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    4. De Bruyn, Arnaud & Viswanathan, Vijay & Beh, Yean Shan & Brock, Jürgen Kai-Uwe & von Wangenheim, Florian, 2020. "Artificial Intelligence and Marketing: Pitfalls and Opportunities," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 91-105.
    5. Abhijit Guha & Dhruv Grewal, 2022. "How robots will affect the future of retailing," AMS Review, Springer;Academy of Marketing Science, vol. 12(3), pages 245-252, December.
    6. Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    7. Madiha Bendjaballah & Christian Dianoux & Sandrine Heitz-Spahn, 2022. "Vers une communication client/vendeur médiatisée par l'usage de l'instrument digital," Post-Print hal-03542762, HAL.
    8. Petar Gidaković & Mateja Kos Koklič & Mila Zečević & Vesna Žabkar, 2022. "The influence of brand sustainability on purchase intentions: the mediating role of brand impressions and brand attitudes," Journal of Brand Management, Palgrave Macmillan, vol. 29(6), pages 556-568, November.
    9. Thomas Cantens, 2023. "How will the State think with the assistance of ChatGPT? The case of customs as an example of generative artificial intelligence in public administrations," CERDI Working papers hal-04233370, HAL.
    10. Francesc Fusté-Forné & Tazim Jamal, 2021. "Co-Creating New Directions for Service Robots in Hospitality and Tourism," Tourism and Hospitality, MDPI, vol. 2(1), pages 1-19, January.
    11. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    12. Luca Dal Bene & Paolo Franchi & Antonella Garna & Giacomo Pieraccioli & Monica Piovi & Paolo Torrico, 2022. "La digitalizzazione dei servizi di supporto in sanità. L?esperienza di ESTAR," MECOSAN, FrancoAngeli Editore, vol. 2022(123), pages 195-209.
    13. Abou-Foul, Mohamad & Ruiz-Alba, Jose L. & López-Tenorio, Pablo J., 2023. "The impact of artificial intelligence capabilities on servitization: The moderating role of absorptive capacity-A dynamic capabilities perspective," Journal of Business Research, Elsevier, vol. 157(C).
    14. Krafft, Manfred & Sajtos, Laszlo & Haenlein, Michael, 2020. "Challenges and Opportunities for Marketing Scholars in Times of the Fourth Industrial Revolution," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 1-8.
    15. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    16. Chang, Woojung & Kim, Kyoungmi (Kate), 2022. "Appropriate service robots in exchange and communal relationships," Journal of Business Research, Elsevier, vol. 141(C), pages 462-474.
    17. Yu-Che Chen & Michael J. Ahn & Yi-Fan Wang, 2023. "Artificial Intelligence and Public Values: Value Impacts and Governance in the Public Sector," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    18. Manjul Gupta & Carlos M. Parra & Denis Dennehy, 2022. "Questioning Racial and Gender Bias in AI-based Recommendations: Do Espoused National Cultural Values Matter?," Information Systems Frontiers, Springer, vol. 24(5), pages 1465-1481, October.
    19. Jean-Éric Pelet & Erhard Lick & Basma Taieb, 2021. "The internet of things in upscale hotels: its impact on guests’ sensory experiences and behavior [L’internet des objets dans l’hôtellerie haut de gamme : son impact sur les expériences sensorielles," Post-Print hal-04137824, HAL.
    20. Rocco, Salvatore, 2022. "Implementing and managing Algorithmic Decision-Making in the public sector," SocArXiv ex93w, Center for Open Science.

    More about this item

    Keywords

    Arteficial intelligence; Cognitive computing systems; Design patterns; AI patterns;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vra:journl:v:11:y:2022:i:2:p:172-183. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pavel Petrov (email available below). General contact details of provider: https://edirc.repec.org/data/uevecea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.