	This review challenges the articles claims that advancement in AI will reduce interpersonal 
interactions, that AI cannot displace active human teachers in education, that in the field of health 
care people and machine will collaborate, and that the current method AI synthesis can be void of bias.
	The study panel claimed that the next generation is increasingly spending more time on their 
devices and are excluding themselves from social interaction. That is only partially correct, and it is 
not the fault of technology but the usage. People who are taught to use technology as a form of resource 
use it interactively with other members of society while next generation who began using technology for 
entertainment use it extensively in solitude to pass time. From experience, college students tend to 
categorize their devices into productivity and entertainment. Productivity usually includes collaboration 
with others while entertainment is used to share with others of similar interests. Face to face 
interaction may decrease but the amount of time associating with people more like oneself has increased. 
	The second challenge is to the statement that human teacher will always be part of the education 
system. The current education system places too much reliance on the abilities of the teacher to be able 
to accommodate the needs of many students. A sufficiently adapted AI will be able to monitor the 
individual students and adjust separately while a human instructor will introduce bias and unnecessities 
into the classroom. The teacher can work side by side with technology but it is not the most efficient 
way in the perspective of a student, nor is it in the interest of the individual students. Human teachers 
will act more on experience and should that contradict the AIs decision then that will result in 
inefficiency and the students will be the ones affected. In effect, it would be more logical to fully 
integrate AI into the education system as the main tool for teaching.
	Similarly, to the last challenge, this one states that in the field of health care physicians 
will collaborate with machines. In simplistic perspective, machines are far more precise than a human can 
be with the 5 senses. A person may be able to intuitively diagnose a patient but AI with a vast data base 
can perform just as well, maybe even better. With the precision and logic of a machine as well as the 
availability of said AI after development, there is no reason to maintain physicians with higher error 
rate. 
	The last challenge is the overall assumption that AI will be fundamentally logical and objective 
in situations where a human would. Much of the current AI training relies on statistics and sample size, 
which is collected and selected by personals with biases. Even devices built to collect data will 
introduce bias from the developer or even the distributor. By developing AI using a human mind we are 
introducing bias to the system. 
	Since most of the article was describing the state of AI in 2030, their claims would stand but 
their basis of AI would be under question. With the current AI technology, considering of advancements in 
the field, it would be hard to categorize the technology as AI since data interpolation is not the same 
as the intelligence of a human mind which was the bench mark for AI. 


