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Despite their past successes, rule-base engines and simple predictive models are not able to identify the majority of fraud attempts anymore. Currently, fraud attempts and breaches are becoming more sophisticated, as the use of machine learning algorithms is finding new ways to defraud digital businesses (Columbus, 2019).

The effectiveness of using artificial intelligence to detect fraud is due to the combined use of supervised and unsupervised machine learning. Supervised machine learning algorithms are designed to learn from example, their training data consists of inputs paired with correct outputs (Wilson, 2019). On the other hand, unsupervised machine learning algorithms infer patterns from a dataset without a paired outcome (DataRobot, 2020). There are three ways in which Artificial Intelligence is revolutionising the field of fraud prevention.

Firstly, AI is causing a shift from relying solely on past experiences to analysing emerging activities, behaviours, and trends in transaction anomalies (Columbus, 2019). If in the past fraud detection systems relied uniquely on past data to detect attempts of fraud, the emergence of artificial intelligence is making the identification and prevention of fraud attempts in real time possible. Today, frauds that usually required up to 8 weeks to be detected, can be immediately recognised thanks to the artificial intelligence technology (Columbus, 2019).

Secondly, artificial intelligence is able to provide fraud analysts with a real-time risk assessment as well as a comprehensive overview of the transaction analysed. Unsupervised machine learning can be utilised in conjunction with anomaly detection to allow analysts to instantly validate or redefine their decisions in terms of acceptable risk and threshold levels (Columbus, 2019).

Finally, AI has the potential to greatly improve the customer’s experience by supporting merchants to easily approve online purchases and reduce false positives (Columbus, 2019). For example, the firm Omniscore provides a transaction safety rating, a score indicating the likelihood that an analysed transaction turns out to be fraudulent. The AI developed by the company analyses hundreds of millions of transactions, their outcomes, their linkages and patterns to help identify good customers, bad customers, and fraudsters (Kount, 2020).

 

References:

Columbus, L. (2019). Top 9 Ways Artificial Intelligence Prevents Fraud. Forbes, [online]. Available at: https://www.forbes.com/sites/louiscolumbus/2019/07/09/top-9-ways-artificial-intelligence-prevents-fraud/#6c04276b14b4 [Accessed 08 October 2020].

DataRobot (2020). Unsupervised Machine Learning. DataRobot, [online]. Available at: https://www.datarobot.com/wiki/unsupervised-machine-learning/ [Accessed 08 October 2020].

Kount (2020). Omniscore Overview. Kount, [online]. Available at: https://support.kount.com/hc/en-us/articles/360045236712-Omniscore-Overview [Accessed 08 October 2020].

Wilson, A. (2019). A Brief Introduction to Supervised Learning. Towards Data Science, [online]. Available at: https://towardsdatascience.com/a-brief-introduction-to-supervised-learning-54a3e3932590 [Accessed 08 October 2020].

 

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In a 2014 interview with the Telegraph, PayPal co-founder and controversial Silicon Valley investor Peter Thiel declared: “I think there are probably three main modes of approaching [death], you can accept it, you can deny it or you can fight it. I think our society is dominated by people who are in denial or acceptance, and I prefer to fight it” (Brown, 2014). Although this claim can be initially dismissed as a fantasy of an eccentric billionaire, an investigation on the current state of the anti-aging technologies might be in order.

The Last Days of Death
For most of our history, humankind has struggled with its own mortality. Despite the numerous legends such as the quest for immortality by the Mesopotamian king Gilgamesh or the Chinese elixirs of life, our ancestors resigned to their inevitable death. However, this is now changing. The scientific and technological community does not think of death as a metaphysical mystery anymore, but as a technical problem that we can and should solve (Harari, 2017).
The emerging current of thought sustains that humans do not die due to a mysterious cosmic plan, humans die due to technical glitches (Harari, 2017). People do not die because of old age, people die of infected lungs, clogged arteries, and heart malfunctions. Death is not anymore the speciality of priests and theologians. Engineers convinced that every technical problem has a technical solution are now taking over (Harari, 2017).
The average life span for early humans was painfully short, only about eighteen years. The average in Roman times was just twenty-five and by 1900, it was only forty-seven in the United States. As humankind became more longevous, our expectations of how many years constitute a full life have changed (Metzl, 2019).

Technological Status
Examples of technologies trying to reverse the aging process are plentiful and diverse. The majority of these innovations are still in their infancy, however, their potential impact on our way of living could be enormous.
Gene therapy appears to be one of the most promising fields in the quest for immortality, numerous trials have been already conducted on mice and some therapies have shown to double their life expectancy (Marr, 2017). Genetic engineers have been more cautious when treating humans, focusing mainly on curing hereditary diseases instead of trying to expand life expectancy. However, this is changing as well, with Libella Gene Therapeutics promising to increase the life span of their clients by twenty years by repairing people’s telomeres (the caps at the end of our chromosomes) at the exorbitant price of $1 million per patient (Gent, 2019).
“Rejuvenation technologies” are emerging as well, with promises of allowing people to act and feel younger for a longer period. The procedure is mainly based on the removal of damaging toxins that are believed to be contributing to the problems of aging (Marr, 2017).
One of the most fascinating fields of regenerative medicine is the field of bioprinting: the creation of human organs from scratch (Pooler, 2019). The process is not dissimilar to 3D printing, artificial organs would solve the problem of shortage of donors and reduce the risk of rejection (Pooler, 2019). Major advancements are expected in this field in the next decades.
Other examples of promising innovations include tiny sensors, AI-assisted diagnosis, custom-made drugs, and nano-robots (Marr, 2017). Too many to be explained in this article.

However, the technological side is probably the easiest component of the question. Will a longer life lead to a happier life? What are the social consequences of all this? Will it increase inequality between the rich and the poor? Is it even a sustainable scenario? These are questions that nobody can answer with certainty yet.

Living longer lives is not about “if” but about “when”. The real question is, are we ready for all this?

References
Brown, M. (2014). Peter Thiel: the billionaire tech entrepreneur on a mission to cheat death. The Telegraph, [online]. Available at: https://www.telegraph.co.uk/technology/11098971/Peter-Thiel-the-billionaire-tech-entrepreneur-on-a-mission-to-cheat-death.html [Accessed 03 October 2020].
Gent, E. (2019). A New Anti-Aging Therapy Is Starting Its First Human Trial – And It Costs $1 Million. Singularity Hub, [online]. Available at: https://singularityhub.com/2019/12/16/a-new-anti-aging-therapy-is-starting-its-first-human-trial-and-it-costs-1-million/#:~:text=Libella%20Gene%20Therapeutics%20says,20%20years%2C%20according%20to%20OneZero.&text=Libella’s%20therapy%20will%20use,%2C%20to%20the%20patients’%20cells. [Accessed 03 October 2020].
Harari, Y.N., 2017. Homo Deus. 2nd ed. London: Vintage, pp. 24-30.
Marr, B. (2017). Will These Tech Innovations Help Us Live Forever? Forbes, [online]. Available at: https://www.forbes.com/sites/bernardmarr/2017/03/31/will-these-tech-innovations-help-us-live-forever/#691f45834d0c [Accessed 03 October 2020].
Metzl, J., 2019. Hacking Darwin. 1st ed. Chicago: Sourcebooks, pp. 131-140.
Pooler, M. (2019). 3D Printing Offers Hope of Building Human Organs from Scratch. Financial Times, [online]. Available at: https://www.ft.com/content/eabb0e00-9755-11e9-98b9-e38c177b152f [Accessed 03 October 2020].