Explainable Artificial Intelligence Essay: Tilburg University

This essay provides an overview of explainable artificial intelligence (AI), highlighting its increasing importance due to the rapid growth of machine learning. It discusses how AI enhances data synthesis and personalized decision-making, referencing examples like Image-Net and sports 1M. The essay acknowledges AI's role in complex tasks such as natural language processing and image recognition, while also addressing the challenges of transparency and accountability. It emphasizes the need for extracting knowledge from AI systems to improve explainability and integrate AI effectively into daily life, stressing the importance of assigning responsibility for AI-related issues within organizations and maintaining compliance with regulations. The essay concludes that while AI presents certain challenges, its ability to mimic human decision-making processes is crucial for promoting internal business growth, advocating for continued efforts to mitigate issues and harness AI's potential.

Running head: EXPLAINABLE ARTIFICIAL INTELLIGENCE
Explainable artificial Intelligence
Student’s name:
Student’s number:
Name of the institution: Tilburg University
Course name: Academic English
Summary
With the prompt emergence of machinery learning technique, artificial intelligence (AI) is also
attaining sustainable growth and being aligned with that of the human performance. AI has
paved the way of synthesizing a large amount of data in a timely and cost effective manner.
Thus, increased stress is being put on the system, based on which AI can be maintained. It is
worthy to mention that, AI plays a very important role in the way of integrating personalized
approach in the way of making any kind of decision.
Samek, Wiegand & Müller (2017) observed that in the era of machine learning, AI is gaining
wide admiration. Rapid development of data based such as image-net and sports 1M are playing
a pivotal role in accelerating human performance. These are some of the significant examples of
AI, which are accelerating the speed of human performance. Preece (2018) highlighted the fact
that there are a wide range of difficult tasks such as assessing the natural languages, regulating
the speech signals and revealing of objects over images, which can be done by AI within a very
limited period of time. Go and Texas hold’em poker are some of the recent revolution of AI,
which can even the professional human players in some of the critical game. Disruptive
innovation is one of the major aspects of AI, which is promoting sustainable growth of both

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industry and the society. However, Preece (2018) counter argued by saying that lack of
transparency is there in AI which often makes it difficult to accelerate human performance. Due
to such lack of transparency, some of the AI models fail to guarantee the human effort. Thus, it is
imperative to interpret the model effectively before initiating any kind of tasks. There are certain
steps, which need to be followed in order to improve AI. According to Samek, Wiegand &
Müller (2017) initially, exact knowledge must be extracted from the AI system, which can have a
firm impact on making the system explainable. This is the way, through which new insight
regarding the system can also be acquired. Daily life of human being can also have a firm impact
on AI. In sum, it can be said that in recent times, artificial intelligence is being affected by the
way of leading daily life. Thus, strict compliance with rules and regulations is very much needed
in terms of overcoming the issues related to AI. Doshi-Velez et al. (2017) put stress on the
ground that in the context of an organization, assigning responsibility to a person at the time of
any kind of negativity of AI is the legal aspect of mitigating any kind of issue of the system.
In recent times, the rate of accountability of AI is increasing in a rapid manner. In the field of
business, academics along with health and social care, the rate of using AI is increasing in a
rapid manner. In addition, AI is also playing a pivotal role in the way of amplifying clinical
decision support system. Explainable artificial intelligence is one of the most emerging types of
artificial intelligence, which helps in making effective decision in daily life. This is basically
human-interpretable procedure, which can have a firm impact on making comprehensive
decision and thereby attain an effective conclusion. An explainable AI presents correct content,
which is key of making a useful decision. Understanding of an explanation is one of the major
factors of explainable AI. This is the way, through which different factors can be assessed
appropriately before making an appropriate decision. Thus, the society must be explore all the

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relevant information that can help in framing comprehensive decision. On the other hand, Preece
(2018) contended by saying that judgment of individual also plays a major role in the way of
taking effective decision.
Based on the discussion, it can be concluded by saying that artificial intelligence is
gaining wide importance in recent times as it is initiating speed in both business and daily human
life. This is playing a pivotal role in enabling the machines to act like human being and thereby
solve any kind of impending task in a timely manner. One of the major role aspects of AI is that
in order to solve any problem and making a comprehensive decision, it always evaluate human
behavior. It is true that, there are certain issues of AI, which are being encountered in recent
times. Still, prompt action must be taken and strong compliance with legislative frame work must
be maintained in terms of mitigating the issues. AI holds the ability to work and take decision
like machines, which is the key of promoting growth in the internal functionality of business.

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References:
Doshi-Velez, F., Kortz, M., Budish, R., Bavitz, C., Gershman, S., O'Brien, D., ... & Wood, A.
(2017). Accountability of AI under the law: The role of explanation. arXiv preprint
arXiv:1711.01134.
Preece, A. (2018). Asking ‘Why’in AI: Explainability of intelligent systems–perspectives and
challenges. Intelligent Systems in Accounting, Finance and Management, 25(2), 63-72.
Samek, W., Wiegand, T., & Müller, K. R. (2017). Explainable artificial intelligence:
Understanding, visualizing and interpreting deep learning models. arXiv preprint
arXiv:1708.08296.