Every September the Dutch ‘prinsjesdag’ will be held. On this day the king speeches about the important cabinet’s plans for upcoming year in the Netherlands. One of the plans is regarding the healthcare costs, and sadly, every year the king announces an increase in these costs. So, it came by no surprise that the forecasted care premium of 2019 will increase by 124 Euros, which results into an estimate of 1432 Euros per year (ANP, 2018). But what causes this annual increase in healthcare cost?

The main cause is the inefficiency of the healthcare industry. Efficiency is described as the maximum feasible level of output for a given set of inputs (Cyclus, Papanicolus, Smith, 2016.). In the healthcare industry, this means that measuring efficiency will be done by the ratio of consumed resources to the valued health system outputs it created. An example of showing the seriousness of inefficiency in the healthcare is consuming excess resources or providing inefficient treatment. This may take away treatment to other patients who could have benefited from the treatment if the resources had been used better. Therefore, to increase the healthcare efficiency, aiming for improvements in resource mobilization and allocation is the solution (WHO, N.A.). Luckily, this can easily be achieved by adopting artificial intelligence (AI) in the whole healthcare industry.

Common artificial intelligences in today’s healthcare are not robots who can perform surgeries on their own, at least not yet. Algorithmic solutions form the everyday artificial intelligence (Pearl, 2018). When doctors and researchers insert data and evidence-based approaches into the algorithms, the computer is able to view and extract the information in order to apply it to a problem. In 2015 doctors were bewildered by a case of an old Japanese women who they thought had acute myeloid leukemia (Kirve, 2018). However, the treatments were unsuccessful for years. Then IBM’s Watson, an AI system, were consulted and found the right treatment. It reviewed approximately 20 million published oncological research studies and cross/referenced data to come to the solution: a rare form of leukemia which could not be detected through conventional methods. When you think about it, it is an enormous waste for the Japanese women to get the wrong treatment for years while the right treatment could have been detected at once by the AI. Therefore, we should not wait to adopt these AI into our whole healthcare industry. Is it not more efficient when AI recommends the treatment first, which can then be verified by the doctors?

References
APN. 2018. ZORGPREMIE VOLGEND JAAR STEVIG OMHOOG DOOR HOGE KOSTEN IN DE ZORG. Retrieved on 5-10-2018 from https://www.nationalezorggids.nl/zorgverzekering/nieuws/44562-zorgpremie-volgend-jaar-stevig-omhoog-door-hoge-kosten-in-de-zorg.html
Cyclus, J., Papanicolus, I., Smith, P. 2016. A framework for thinking about health system efficiency. Retrieved on 5-10-2018 from https://www.ncbi.nlm.nih.gov/books/NBK436891/
Kirve, P. 2018. Can artificial intelligence give us a more efficient health care system? Retrieved on 5-0-2018 from https://geneticliteracyproject.org/2018/09/10/can-artificial-intelligence-give-us-a-more-efficient-health-care-system/

Pearl, R. 2018. Artificial Intelligence In Healthcare: Separating Reality From Hype. Retrieved on 5-10-2018 from https://www.forbes.com/sites/robertpearl/2018/03/13/artificial-intelligence-in-healthcare/#2767dc661d75
WHO. N.A. Addressing health system inefficiencies. Retrieved on 5-10-2018 from http://www.who.int/health_financing/topics/efficiency/system-inefficiencies/en/

In this digital age humans give more and more manual tasks away. We programmed the computer to automatically execute certain duties as it provides a higher level of efficiency and accuracy. However, how far should we allow artificial intelligence to take over human tasks?

1.5 years ago a bricklaying robot called SAM, developed by a New York construction company, can layer 300 to 400 bricks per hour, whereas a stone mason lays 60 to 75 bricks per hour (Javelosa & Reedy, 2017). In the future our houses may actually be built by robots as they perform the task 5 times faster. This is a great illustration of how robots are capable of providing services and goods quicker than humans in this hustle world. However, several years ago people wanted to develop something more advanced than drones. They might have gotten some inspirations from movies like Terminator or games like Detroit become human which on a side note is a really good PlayStation game, and came up with killer robots. Killer robots are autonomous weapon systems that could target and attack an object or person without any human control (BBC, 2018). According to Cambridge’s definition of ‘autonomous’, it refers to having the power to make decision independently (Cambridge Dictionary, N.A.). This implies that killer robots could actually kill a person without command. Luckily, these robots do not exist, not yet. But their precursors do. For example, semi-autonomous robots are already patrolling at the South-North Korea border which can be switched to autonomous mode (Wakefield, 2018).

This week the European Parliament held a meeting about these killer robots (Nu.nl, 2018), and while there are a lot of oppositions in the EU towards the killer robot and supporters of banning the robot, several countries including Korea, China, England, America and Russia are interested in the idea of killer robots and want to explore the possibilities of autonomous weapons. Imagine that these killer robots actually exist, isn’t it complicated to point out whose responsibility it is when an incident occurs? And isn’t it difficult to say that these robots can separate soldiers and citizens well during a war? Lastly, shouldn’t we just ban these killer robots completely because humans should never give the decision about life and death away to an emotionless robot.

References:
BBC.com (12 September 2018). MEPs vote to ban killer robots on battlefield. Retrieved on 13-09-2018 from https://www.bbc.com/news/technology-45497617.

Cambridge Dictionary (NA). autonomous. Retrieved on 13-09-2018 from https://dictionary.cambridge.org/dictionary/english/autonomous.

Javelosa, J. & Reedy, C. (7 April 2017). Brick By Brick. Retrieved on 13-09-2018 from https://futurism.com/this-robot-works-500-faster-than-humans-and-it-puts-thousands-of-jobs-at-risk/.

Nu.nl (12 september 2018). Europees parlement wil killer robots verbieden. Retrieved on 13-09-2018 from https://www.nu.nl/tech/5459102/europees-parlement-wil-killer-robots-verbieden.html.

Wakefield, J. (5 April 2018). South Korean university boycotted over ‘killer robots’. Retrieved on 13-09-2018 from https://www.bbc.co.uk/news/technology-43653648.