Cultural Awareness in Ethical AI: Addressing Ethical Dilemmas Globally

Science fiction roots: throughout fantasy and science fiction stories, robots and other automatons appeared and in the first half of the 1900s, the idea of artificially intelligent beings seeped into the minds of scientists and mathematicians alike, thanks to characters such as the Tin Man from Frank L Baum’s The Wizard of Oz. Great mathematicians, scientists, and philosophers started to grapple with AI as a possibility in the 1950s; one such example of such an individual would be mathematician Alan Turing who published “Computing Machinery and Intelligence.” But science wasn’t technologically ready to pursue that endeavor…yet. 

Ahead of their time: the first program that focused on artificial intelligence called the Logic Theorist was presented in 1956 at the Dartmouth Summer Research Project on Artificial Intelligence, where experts from around the globe met to discuss what they envisioned for the future of autonomous machines. The term artificial intelligence was coined by John McCarthy there and although he had hoped that the conference would achieve more, it did successfully unite these experts, motivate them to research AI, and make them believe that it was a real possibility. 

Does not compute: computers continued to improve and grow in power; however, they were still not where they needed to be to run more complex algorithms. Machine learning algorithms were slowly and steadily becoming more accurate and useful for all types of problem solving and governments started to see the value of artificial intelligence in the long term thanks to Moore’s Law, which stipulates that computing power such as memory and speed doubles annually. In the 1980s, there was some advancement when two experts named John Hopfield and David Rumelhart released their deep learning techniques that gave computers the opportunity to learn, thanks to experience. 

A chess match: Although some governments invested millions of dollars in AI programs, there was little progress made until the mid 1990s when IBM’s Deep Blue, a chess playing computer program, defeated Gary Kasparov, the reigning world chess champion. In the same year, Windows incorporated a speech recognition program developed by Dragon Systems onto their software; machines were entering a stage of development that surpassed human capabilities and allowed machines and humans to interact beyond a mere keyboard.

The age of big data: when computers and other devices reached sufficient computing power to handle artificial intelligence, it was time to take advantage of all the effort and research from scientists and AI experts. Businesses and companies have become more efficient and influential, thanks to the use of machine learning, artificial intelligence, and complex algorithms and these tools are now essential parts of their businesses. Collecting and analyzing the data from people’s devices, software can show you a world full of products that you want to see.

Healthcare diagnosis and treatment

Medication development and discovery

Remote healthcare assistance

Chatbots and virtual assistants

AI-driven recruitment programs

Data analysis and insight generation

Financial decision-making

Forecast and weather modeling

Creative content creation

Cybersecurity solutions

Customer service and personalized marketing

Self-driving vehicles

Educational platforms

Infrastructure management 

Accountability: when a self-driving car makes a decision that could cost lives, who will be the responsible party? Artificial intelligence takes action autonomously based on the data available without human oversight, so when it does make a choice that does harm, the liability needs to fall on someone’s shoulders. Determining who takes the blame is paramount and transparency into how AI reaches these decisions is an important point that could also build trust and settle this issue.

Employment: since AI has become so powerful, it’s crucial we think about how its automated processes could potentially complete the job of a human being and make their position redundant and unnecessary. This will cause unemployment for many and  have a huge impact on society and the economy down the road if we don’t prepare future generations to take jobs that won’t become redundant and upskill and reskill professionals that are already in the workforce. Mass unemployment is a real possibility in the future; however, with the proper preparation, society can mitigate its effect.

AI bias: although most don’t mention bias in artificial intelligence, one of the biggest issues surrounding its capabilities is the information it presents to its users. The job of these sophisticated machines and programs is to sift through a continuous stream of data and when the data is biased, the results are also equally as skewed. Consequently, AI may perpetuate and further spread these societal biases, impacting employment, education, finances, social media, and more. Society already has a huge problem with biases and addressing this issue is an important step in ensuring that humanity doesn’t allow AI to aggravate our societal problems further.

Data security: as we have already seen, artificial intelligence is constantly taking and analyzing our data to help make their decisions and learn more and simultaneously, we are allowing companies and social media to constantly access and collect that data. Whenever we search for something on applications, we are providing them with data about ourselves and a major concern for AI is our privacy. With the everyday use of our personal devices and interaction with the internet, we must protect our private data and striking a balance between artificial intelligence’s need for data and our own privacy is a difficult task that still hasn’t been solved.