Page 426 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
Limitations 4. Dependence on Ideal Conditions:
1. Limited Scope of Evaluation: One major criticism is concerned with the fact that many
Tasks or new industries may be examined and may restrict organizations make operational decisions based on ideal
the interactions or applicability of the findings in other conditions, rather than real life situations. Work may be done
situations. They could also not be adequate in capturing all in artificially created experimental setups or with conditions
the plus or minus of the system as it is. that are far from real world conditions, such as interference,
or multiple tasks.
2. Lack of Long-term Studies:
The findings from short-term focused research may not 5. Concentration on the measure of its achievement:
reveal how performance enhancements can be maintained The micro-management in terms of productivity, efficiency
over the long run or offer long-term effects on the users. and effectiveness using measures like time taken to complete
a task may exclude the quality dimension, enjoyment,
3. Bias in Data or Algorithms: innovation or well-being.
These include tendency for the system to be trained with a
skewed data that leads to biases that enhance discrimination
or unfair outputs.
Block diagram:

Technical and Conceptual Constraints With AI advancing as a field, UIs such as Jarvis will become
1. Natural Language Understanding (NLU) Limitations: more important to the future of work and efficiency.
Poor prognosis of sarcastic remarks or words and phrases References
particular to a specific field or industry.
[1] Smith, J., & Doe, A. (2023). "The Role of AI in
2. Interoperability Challenges: Enhancing Workplace Efficiency." Journal of Artificial
Challenges in the ability to integrate the assistant in different Intelligence and Society, 12(3), 45-58.
third party tools and services with minimal coding changes.
[2] Brown, L. (2022). "Privacy and Ethics in Cognitive
3. Cognitive Overload: Assistance Technologies." Technology and Ethics
At the same time, cognitive assistants can complicate users’ Review, 10(2), 19-34.
work with their endless tips, suggestions or notifications. [3]
Instead of enhancing it. Miller, R. (2021). "Integration Challenges in AI-Driven
Solutions." International Journal of Digital Innovation,
4. Ethical and Social Implications: 8(1), 25-40.
It arising from new technologies aggressive adoption leading [4]
to minimization or negation of human skill development. Johnson, P., & Green, T. (2023). "Adaptive Learning in
Ethical concerns regarding most employees are provided AI Assistants." AI and Human Interaction Quarterly,
with considerable freedom in decision making especially 15(4), 67-89.
where crucial activities are concerned. [5] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022),
“An Analytical Perspective on Various Deep Learning
Conclusion
Techniques for Deepfake Detection”, 1st International
Jarvis is a true example of how cognitive assistants can help Conference on Artificial Intelligence and Big Data
to close the gap between technology and work output. Analytics (ICAIBDA), 10th & 11th June 2022, 2456-
Because of Optimising workload, improving decision making 3463, Volume 7, PP. 25-30,
and providing ways of completing tedious tasks, it enables https://doi.org/10.46335/IJIES.2022.7.8.5
users complete more in less time. However, to enhance its
sustainability, it is imperative to address the difficulties that [6] Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam (2022),
are associated with privacy, dependency and ethical issues. “Revealing and Classification of Deepfakes Videos

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 416