Artificial Intelligence (AI)

Artificial intelligence (AI) has the potential to be extremely beneficial in the therapy of communication barriers in autistic children. An artificial intelligence-based program has the potential to improve children's social abilities through more contact, consequently boosting their communication quality. Apart from treatment, AI can detect early indicators of autism in youngsters and take preventive measures to correct or at least lessen them (Vlasits, 2017). In this persuasive study, artificial intelligence is presented as a possible solution to autism. Furthermore, this paper defends the counterarguments against the viability or justification of the applicability of the solution for the cause of children.


Autism Spectrum Disorder (ASD), most commonly known as the autism, is an extreme developmental disorder mostly seen in children, which prevent children from developing social skills and non-verbal communication. Children who are diagnosed with autism are highly likely to face challenges in carrying out social activities and interaction with people, which often cause withdrawal from the environment. They tend to live an isolated life and develop more health consequences due to social separation (HelenTager-Flusberg & ElizabethCaronna, 2007). The level and type of autism may vary widely among children but the problem of communication barrier is common among almost all of them.

Though there is no known cure or treatment to the disease, early detection and behavioral therapies are two of the most common line of defenses against the highly disruptive disease. Researches show that early detection and intervention can greatly help in reducing the severity of the disease (Handleman & Harris, 2000). Behavioral therapies in the form of interactions and small communication can improve the learning curve of children (Vicker, 2016). However, since the spectrum of the disease varies widely and each autistic child responds differently to intervention, it is highly challenging for caregivers and healthcare professionals to come with a perfect care plan to treat the disease. Design of a good intervention plan requires analysis of children’s behavior and response to specific behavioral therapies, which is time consuming and highly challenging for human healthcare professional (JavierVirués-Ortega, 2010). In this case, artificial intelligence based intervention can do a miracle. Artificial intelligence can integrate humanly perceptions and understanding with the working excellence of machine. It can perform visual perception, speech recognition, language translation, and decision making. It has the ability to learning through induction process and modify its actions based on the feedback it receives (Harris, 2010). The utilization of artificial intelligence can be phenomenal in early detection and intervention of autism in children as it utilizes highly sophisticated and responsive techniques to mitigate the effect of autism and help children live with the disease efficiently. This paper will focus on different possibilities about how Artificial Intelligence based technologies and applications can improve the treatment of autistic kids.

Artificial Intelligence in Improving Communication Barrier in Children with Autism

The development of AI-based applications and techniques can improve the process of treating and detecting autism for children. However, there are also come drawbacks to those applications that must be overcome to make the results happen in real life. Artificial intelligence has its own limitations, which prevents widespread adoption of the technology for the treatment of autism. The technology is still under development and has many technical issues that are to be solved to prescribe it as a panacea for autism. However, despite these facts, artificial intelligence is the most optimistic probabilities to deal with the highly challenging medical cause in the most proficient manner.

One of the most prevailing counterargument against using AI for the treatment of autism is that AI itself possesses large threat to the existence of human race in the future. Employing AI in the treatment autism might be proved to be a self-destructive proposition as it might learn about one of the most damaging weaknesses of human and try to exploit it for its own good. Elon Musk of Tesla Motors and Stephen Hawking have been constantly warning about the emergence of AI and its possible takeover on human race (Riley, 2015). The idea of distributed AI will have the ability to share information between multiple AI’s where all the AIs will be acting as a single brain. In that cases, using AIs for the treatment of diseases might be dangerous as they can exploit human by many ways.

However, this counterargument is not alarming, at least not for the time being. It will take a few more decades for artificial intelligence to outsmart us so we do not have to worry about it now. Also, with proper implementation of ethics for artificial intelligence, such a scenario is definitely avoidable. The concept of AI is dangerous as it may but we have not developed such an AI that can take control over us due to lack of development breakthrough or due to lack of capability. We have seen many industrial line robots and laboratory based AI that have the potential to learn from the environment and go beyond their scope of work. But such occurrences either did not happen or never been reported. The book name Machine Ethics may be considered to be a good resource for studying about machine ethics that are built to prevent machines going beyond their line and take harmful actions on human race. The excerpt of the book suggests that the machine ethics has been an emerging topic that is evolving rapidly to put a demarcation line between what Artificial Intelligence based machine should do and should not do (Anderson & Anderson, 2011). Reaching a level of development where we will be needing to really concerned about AI is far away; we can present the evidence that currently AI is not able to even break CAPTCHA, which is an incredibly trivial task for human. Therefore, it is way too early to be worried about them and not exploiting benefits of them in fear of their adversary.

In his article, Russel (2015) tries to explore the potential of artificial intelligence in shaping future of human race while keeping it restricted by the implementation of ethics. The article suggests a human-machine collaborative environment where machine will be taught to think human being as their complementary and supportive rather than a threat to their existence. By doing so, we can make AI support rather than rival to us (Russell, 2015).

With its enormous processing power and advanced learning algorithm based on extensive research, AI can help us understand autism better. Currently, robot helps social skills for autistic children. Artificial intelligence driven robots can read and understand the behavior of autistic children and respond accordingly. They are more predictable than human counterpart and thus create a comfortable environment for children with special care need. With future development in AI, these robots will be a breakthrough for children with autism in breaking the barriers of communication.

Currently, in many facilities, robots are directly helping autistic kids by playing with them or teaching them how to do basic social skills. Researchers focus on developing novel working principles for the different types of AI robots to help autistic children develop their social ability and overcome communication behavior. The incorporation of AI has revolutionary impact on the performance and outcome of the project as they are simply analyzing autistic children behavior and respond in an appropriate manner to make them feel at home (Dong & Zhao, 2016).

If AI is the tool then genetics is the answer to many autism related issues. Scientists yet to discover the true cause of autism as the disease is a complex combination of multiple factors, of which erratic genome code is prominent. Through the use of AI, it is possible to analyze DNA information of a large population of human to reach a conclusive evidence about the root cause of the disease. An AI can be taught to find patterns in DNA of autistic children that might be cause of the disease. Through appropriate design, a researcher can teach the AI how to read genome code, how to find anomalies, and how to isolate the problematic genes. Only through the use of AI, these researches can be done because the volume of computation involved is extraordinarily high (Pennisi, 2017).

AI can help autistic kids developing their social skills by providing multiple ways of interacting with them. Robot have more opportunities to help in building social skills in autistic children. AI is better at spending time with children, playing with them, keeping track on their development, and changing course of actions in response to the rate of development. In many cases, AI can create favorable learning environment around the children, suggest factors for improved learning, and create an enthusiastic place for learning for children. Specially designed AI robots are already helping autistic kids by playing with them or teaching them how to do basic social skills (Dong & Zhao, 2016)

Virtual Reality Social Cognition Training for children with high functioning autism is a new era developed by exploiting the ability of AI to emancipate virtual reality based on the special needs of autistic children, which has high rate of success in mitigating communication barrier in extreme level autism (Didehbani, Allen, Kandalaft, Krawczyk, & Chapman, 2016). By emerging in the virtual reality world and interacting with AI-based peers, autistic kids will have a much safer place to train themselves in while the therapists have more control over the environment. Moreover, Artificial Intelligence also introduces new techniques to help diagnose children with autism faster which eventually lead to more efficiency treatments to improve autistic children’s communicative ability. AI predicts autism from infant brain scans. Researchers have developed new ways of implementing AI in detecting autism related communication barrier accurately before even the children start communicating (Scudellari, 2017).

The use of artificial intelligence makes it possible to shorten the behavioral diagnosis of autism. This is an example about how the diagnosis method can be shortened significantly without reducing its accuracy. By making use of the ADTree, the authors reduced a 2 hours long diagnosis process into a 5 minute one which can be taken on the internet. This also enables more children to take the test (DP, R., R, J-Y, & TF, 2012).


In the end, Artificial Intelligence will certainly help autistic children to communicate better by improving their social skills. Even though there might be struggles for this technology in the future, the potentials that AI bring are overwhelming. It is high time to spend more effort and money in investigating how effectively AI can be involved in the treatment and diagnosis of autism related communication behavior for better outcome.


Anderson, M., & Anderson, S. L. (2011). Machine Ethics. Cambridge University Press.

Didehbani, N., Allen, T., Kandalaft, M., Krawczyk, D., & Chapman, S. (2016). Virtual Reality Social Cognition Training for children with high functioning autism. Computers in Human Behavior, 703-711.

Dong, X., & Zhao, Y. (2016, April 26). Robot helps social skills for autistic children. USA Today.

DP, W., R., D., R, L., J-Y, J., & TF, D. (2012). Use of Artificial Intelligence to Shorten the Behavioral Diagnosis of Autism. PLoS ONE.

Handleman, J. S., & Harris, S. L. (2000). Preschool Education Programs for Children With Autism. Pro Ed.

Harris, M. C. (2010). Artificial Intelligence. Marshall Cavendish.

HelenTager-Flusberg, & ElizabethCaronna. (2007). Language Disorders: Autism and Other Pervasive Developmental Disorders. Pediatric Clinics of North America, 469-481.

JavierVirués-Ortega. (2010). Applied behavior analytic intervention for autism in early childhood: Meta-analysis, meta-regression and dose–response meta-analysis of multiple outcomes. Clinical Psychology Review, 387-399.

Pennisi, E. (2017). Combing the genome for the roots of autism. Science, 357.

Riley, C. (2015, July 28). Elon Musk and Stephen Hawking warn over 'killer robots'. CNN.

Russell, S. (2015). Ethics of artificial intelligence. Nature.

Scudellari, M. (2017). AI Detects Autism in Infants (Again). IEEE Spectrum.

Vicker, B. (2016, October 24). Social Communication and Language Characteristics Associated with High Functioning, Verbal Children and Adults with ASD. Retrieved on October 13, 2017 from Indiana Resource Center for Autism:


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