It is predicted that soon machines will be able to do many complicated tasks, and in the process, surpassing humans in the workforce (Agrawal et al., 2019). In my view, I do not support the replication of the human touch in Artificial Intelligence (AI) devices by developers. In this paper, I will argue why replication of the human touch is complicated, and it will have more harm than good in regards to employment.
There is still a long way before AI can completely replace humans, considering that it is a complicated task to give AI devices a human touch. Some tasks performed by AI devices are hard to implement, especially those that require the use of information that is not in the database. When in a situation where instant decision making is required, AI devices lack the ability to use sense, unlike human beings. For example, in the case of controlling riot or a disturbance, AI bot will have to refer to its programmed database to decide whether to use force based on experience (Millington & Funge, 2018). In the example, AI bot can harm a journalist who is covering the riot, unlike a police officer who can make a judgement before acting. In another example, when one walks into a hospital, nurses will, in most cases, cheer you up by being friendly and caring. For developers, it will be challenging to achieve human touch, such as showing emotions of caring, loving to an AI bot. Humans will show genuine care through friendly interactions, while an AI bot will only do so through programmed algorithms (Calum, 2018).
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Replicating human touch in AI will be achieved through independent reasoning in decision making, and efficient social interactions by the bots. In conclusion, developers should think of ways of building AI bots that do not undermine humans but instead improving skills by working alongside humans.
References
Agrawal, A., Gans, J., & Goldfarb, A. (2019). Artificial intelligence: The ambiguous labor market impact of automating prediction. https://doi.org/10.3386/w25619
Calum, C. (2018). How to make an artificial general intelligence. Artificial Intelligence and the Two Singularities , 103-119. https://doi.org/10.1201/9781351254465-7
Millington, I., & Funge, J. (2018). Decision making. Artificial Intelligence for Games , 293-491. https://doi.org/10.1201/9781315375229-5
