Technology & Management Review

Peer Reviewed Article

Vol. 4 (2019)

Explainable AI: Meeting Transparency and Accountability Demands in Data Science

Published
2019-05-30

Abstract

As artificial intelligence (AI) continues to permeate various aspects of society, the demand for transparency and accountability in AI systems, particularly in the context of data science, becomes increasingly critical. This article delves into the challenges and imperatives of achieving explainability in AI, addressing the ethical concerns associated with opaque algorithms. We explore the current landscape of Explainable AI (XAI) techniques and methodologies, evaluating their efficacy in meeting the growing demands for transparency. Additionally, the article discusses the role of explainability in fostering accountability, not only in algorithmic decision-making but also in shaping policies and regulations that govern AI applications. Through a comprehensive examination of real-world cases and emerging standards, we aim to provide insights into the evolving intersection of Explainable AI, transparency, and accountability in the dynamic field of data science.

References

  1. Achar, S. (2015). Requirement of Cloud Analytics and Distributed Cloud Computing: An Initial Overview. International Journal of Reciprocal Symmetry and Physical Sciences, 2, 12–18. Retrieved from https://upright.pub/index.php/ijrsps/article/view/70
  2. Dekkati, S., & Thaduri, U. R. (2017). Innovative Method for the Prediction of Software Defects Based on Class Imbalance Datasets. Technology & Management Review, 2, 1–5. Retrieved from https://upright.pub/index.php/tmr/article/view/78
  3. Dekkati, S., Thaduri, U. R., & Lal, K. (2016). Business Value of Digitization: Curse or Blessing?. Global Disclosure of Economics and Business, 5(2), 133-138. https://doi.org/10.18034/gdeb.v5i2.702
  4. Deming, C., Dekkati, S., & Desamsetti, H. (2018). Exploratory Data Analysis and Visualization for Business Analytics. Asian Journal of Applied Science and Engineering, 7(1), 93–100. https://doi.org/10.18034/ajase.v7i1.53
  5. Fadziso, T., Adusumalli, H. P., & Pasupuleti, M. B. (2018). Cloud of Things and Interworking IoT Platform: Strategy and Execution Overviews. Asian Journal of Applied Science and Engineering, 7, 85–92. Retrieved from https://upright.pub/index.php/ajase/article/view/63
  6. Kaluvakuri, S., & Amin, R. (2018). From Paper Trails to Digital Success: The Evolution of E-Accounting. Asian Accounting and Auditing Advancement, 9(1), 73–88. https://4ajournal.com/article/view/82
  7. Kaluvakuri, S., & Lal, K. (2017). Networking Alchemy: Demystifying the Magic behind Seamless Digital Connectivity. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 20-28. https://upright.pub/index.php/ijrstp/article/view/105
  8. Lal, K. (2015). How Does Cloud Infrastructure Work?. Asia Pacific Journal of Energy and Environment, 2(2), 61-64. https://doi.org/10.18034/apjee.v2i2.697
  9. Lal, K. (2016). Impact of Multi-Cloud Infrastructure on Business Organizations to Use Cloud Platforms to Fulfill Their Cloud Needs. American Journal of Trade and Policy, 3(3), 121–126. https://doi.org/10.18034/ajtp.v3i3.663
  10. Lal, K., & Ballamudi, V. K. R. (2017). Unlock Data’s Full Potential with Segment: A Cloud Data Integration Approach. Technology & Management Review, 2(1), 6–12. https://upright.pub/index.php/tmr/article/view/80
  11. Lal, K., Ballamudi, V. K. R., & Thaduri, U. R. (2018). Exploiting the Potential of Artificial Intelligence in Decision Support Systems. ABC Journal of Advanced Research, 7(2), 131-138. https://doi.org/10.18034/abcjar.v7i2.695
  12. Maddali, K., Roy, I., Sinha, K., Gupta, B., Hexmoor, H., & Kaluvakuri, S. (2018). Efficient Any Source Capacity-Constrained Overlay Multicast in LDE-Based P2P Networks. 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Indore, India, 1-5. https://doi.org/10.1109/ANTS.2018.8710160
  13. Thaduri, U. R., Ballamudi, V. K. R., Dekkati, S., & Mandapuram, M. (2016). Making the Cloud Adoption Decisions: Gaining Advantages from Taking an Integrated Approach. International Journal of Reciprocal Symmetry and Theoretical Physics, 3, 11–16. https://upright.pub/index.php/ijrstp/article/view/77

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