Artificial Intelligence: A Pandora’s Box?
Tags: AI, Machine Learning, Discrimination, Bias, Ethics

Pandora’s Box

Imagine that you are in a ride of a driverless car going to a date hooked up by a matching site. Or, in a different scenario, one of your mates has been diagnosed having a stroke via a deep learning medical diagnosis system. Many people may have a similar question: should these artificial intelligent (AI) technologies be trusted on our lives or the lives of our loved ones? It has opened up a big can of worms. Some are excited and buoyant about this technological advancement and would try to make good use of it if possible, while others are not so enthusiastic about it. Critics argue that such a technology could potentially be misused in various ways, such as policing or weaponisation, and could be vulnerable for hacking.

Automated Vehichle

Speaking of AI, many people would start with the current rising technology of automated vehicles. In the hope of a safer road shared by passers-by and vehicles, quite a few tech companies are developing automated vehicles which have shown promising results; however, current self-driving technology still fails to prevent traffic accidents, as some car crashes had occurred by self-driving cars during the test trials, including the deaths of a pedestrian, cyclist and driver. That is why official organisations, like the European Commission, suggest thorough discussions for better design standards and production guidelines of Connected and Automated Vehicles (CAVs), as well as the laws and regulations of their use on the road. So, both passengers and pedestrians would feel safer with CAVs operating in public. For a similar reason, AI for Good Global Summit addressed ethical thinking and introduced the Molly Problem, where people were asked to answer an online survey on what actions a driverless car should take in a car collision. In some questions of the survey, participants would have to choose to save between the pedestrian on the road and the passenger in the car. With such a heavy topic, researchers, experts, lawmakers and associations would likely have to discuss all kinds of issues on automated automobiles before those vehicles go above and beyond.

Not just self-driving automobiles, people are trying to put their intimate lives on the hand of AI algorithms as well. With the rise of the internet, many are heading to dating sites for a mate, like eHarmony, Tinder or OKCupid, as most of us are living in a hectic lifestyle nowadays and hope that these sites could help us find a match with ease. Apart from their convenience, many matching platforms have a trust problem with some researchers on the bias and discrimination, as those platforms recommend matches based on user’s race, age, political view and other factors. Certainly, some psychologists from multiple US universities had conducted a joint study that attempts using a machine learning (ML) algorithm, Random Forests, to predict human mating interest. Although the research sample is small and narrow (just above 150 mixed-gender bachelor students in their early 20s), the study shows that the algorithm cannot accurately make the relationship prediction among samples. To put it simply, the current mathematical calculation is not yet figuring out human’s nature of love.

Another case scenario is healthcare. Undeniably, ML-based tools have become widely used in various industries for efficiency and low-cost, including the healthcare sector. In the Medicaid waiver program in the US, for example, patients’ cases were assessed by an algorithmic system to allocate care and funds, but soon after, this system was under fire due to complaints that patients received healthcare fund cuts caused by predictor biases in algorithms. Similarly, contributed by imbalanced datasets used during the training process of AI-based medical devices and tools, incorrect diagnosis and medical mismeasurement are becoming so concerning that Food and Drug Administration (FDA) lately proposed a regulatory framework for such devices and tools using AI or ML to maintain an equal and fair healthcare system for each patient in the US. It seems that a small predictor bias in medical software determines the life and death of a patient.

Sourced from BBC news

Besides healthcare, ML has also been introduced to other public sectors, like law enforcement. Understandably, AI technology could be used in crime detection and forensic science for its extraordinary performance in data classification and clustering, but it also raises social controversies and outcries. For instance, an African American was under arrest mistakenly due to the racial bias of the facial recognition technology used in the Detroit police department. A Chinese driver received a ticket as he was wrongfully identified using a mobile phone while driving by a traffic camera and AI recognition system, but in fact, he was scratching his face. Due to these negative news, some tech giants, like IBM, Amazon and Microsoft decided not to develop facial recognition technology or not to provide such products to law enforcements until relevant regulations have been set. So, object recognition seemingly could be a good tool for police’s investigation, but it is flawless. They should not simply jump to the conclusion based on the system results.

In a new level, AI has been weaponised. According to an article Global Policy in 2019, The Artificial Intelligence Arms Race: Trends and World Leaders in Autonomous Weapons Development, there is a massive investment in warfare weapon systems with advanced AI technology, like armed robots and drones, among several countries and regions, including the United States, China, Russia and the European Union. With such a lethal power in hands, unfortunately, few discussion had been made regarding the ethics of using these smart weapons. With high accuracy but yet biases, innocent civilians would become incredibly vulnerable when facing these cold and bloodless AI killers.

And yet, every sun has its dark spots. Without a doubt, machine learning is a powerful technology so far, but it could be vulnerable to hacking too. Here comes the nightmare of ML, adversarial machine learning, which is a technique to fool and manipulate the models to produce false outputs, or worse, cause financial loss. It includes taxonomy, evasion, poisoning and model stealing. If a machine learning related vulnerability of public infrastructures or a warfare weapon had been exposed in a wrong hand, the consequences could be catastrophic.

To answer the question in the title, my answer is yes and no. Even though AI or ML is the future of the world, I strongly believe that relevant ethics and standards are as important as bread and button in the digital era. Therefore, more public discussion on this matter is needed.

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