Part 3 of 3 | Chronicle of Artificial Intelligence
Humans vs AI: The Future
Experts’ Opinions, predictions, and possible roadmap to our Co-existence
We’ve covered the journey of Artificial intelligence to its current state.
We learned the differences and similarities between humans, and their magnum opus, AI.
But now, at the helm of a flourishing AI spring, how do we see the future of our co-existence?
That’s what we are going to explore in this final part of the chronicle of Artificial Intelligence.
Part 1
Part 2
Artificial Intelligence (AI) has come a long way from being a concept to becoming a reality. It has already changed the way we live and work. It has revolutionized almost every aspect of our lives, from healthcare to entertainment to education. But as we embrace AI, we should also be aware of the potential risks it poses to our society and the world. Here are some of the most significant concerns about AI’s impact on our lives:
“We need to be super careful with AI. Potentially more dangerous than nukes.” — Elon Musk
“The development of full artificial intelligence could spell the end of the human race.” — Stephen Hawking
Unemployment: AI may take over human jobs
One of the biggest concerns about AI is that it may replace human workers. As AI continues to develop and improve, it can perform many tasks more efficiently than humans. For example, Amazon has already started using robots in their warehouses. They pack and ship products, replacing human workers. Another AI-driven massive unemployment came with the automation of the automotive industry. In the early 2010s, car manufacturers began investing a lot in robots and automation. This was an attempt to increase efficiency and reduce costs. According to a report by McKinsey, up to 800 million jobs worldwide could be lost to automation by 2030.
Bias: AI can perpetuate and amplify human biases
AI algorithms are designed and trained by humans, and they may inherit human biases. This can lead to biased decision-making by AI systems, which can be detrimental to certain groups of people.
One striking example of this was the case of Amazon’s recruitment algorithm. In 2018, Amazon developed an AI-powered recruiting tool that was biased against women and people of color. For instance, the algorithm downgraded resumes that included the word “women’s,” such as “women’s chess club captain”. It penalized graduates of two women’s colleges. The system also gave high rankings to candidates who played lacrosse. A sport more commonly played by men in the United States.
Security: AI used for cyberattacks and other malicious purposes
AI can be used for malicious purposes, such as cyberattacks or even physical attacks. For example, hackers can use AI to generate realistic phishing emails. This can trick people into revealing their personal information. AI can also be used to control drones or other autonomous weapons, which can cause harm to people.
One hair-raisin example of the use of AI in a cyberattack came in the 2019 incident. An AI-powered deepfake audio impersonated the CEO of a UK-based energy firm. It tricked a manager of the firm into transferring €220,000 ($243,000) to a Hungarian supplier. The use of deepfake audio technology allowed the attacker to bypass traditional security measures. They avoided layers of security such as two-factor authentication or face-to-face communication. This resulted in a successful impersonation of the CEO’s voice and raised a giant flag.
Ethics: AI raises ethical concerns
AI raises ethical concerns, such as the use of autonomous weapons or the impact of AI on privacy. AI can collect and analyze a lot of personal data, which can infringe on privacy rights. A paper by philosopher Nick Bostrom argues that super-intelligent AI could pose an existential risk to humanity. If, it is programmed with the wrong goals.
Technological Dependencies: Too much reliance on the algo
The risk of too much technological dependence on AI can be fatal. It can lead to a lack of human decision-making and critical thinking. Humans may become complacent and fail to consider alternative perspectives or solutions.
One example of this risk arose in the 2019 Ethiopian Airlines Flight 302 crash. The Boeing 737 Max, crashed shortly after takeoff and killed all 157 people on board. Investigations revealed that a malfunctioning sensor on the aircraft had triggered an automated system known as the Maneuvering Characteristics Augmentation System (MCAS). Which pushed the nose of the plane down, overriding the pilots’ attempts to correct it. The pilots were unable to regain control of the aircraft before it crashed.
Unintended Consequences: Undesired results
This risk is a significant concern in the development and deployment of AI systems. These consequences occur when AI systems produce unexpected results. Results that could be harmful to individuals or society as a whole. And it’s often due to biases or limitations in the data used to train the systems. For instance, a study conducted by ProPublica in 2016 found that a predictive policing algorithm used by the US state of Florida incorrectly identified African American defendants as having a higher risk of committing future crimes than white defendants.
Environmental Impacts: Massive energy consumption and E-wastes
There are also several environmental risks associated with AI that we must address. AI algorithms need large amounts of computing power and data storage. This can lead to a significant increase in energy consumption. That, in turn, can lead to increased greenhouse gas emissions and contribute to climate change.
Energy consumption:
According to a report by Greenpeace, global data center electricity consumption is projected to reach 651 terawatt-hours (TWh) by 2030. This would represent about 5.6% of global electricity consumption. The report also notes that the carbon footprint of data centers could to grow from 200 million tons of CO2 equivalent in 2018 to 278 million tons by 2025. Which is equal to the emissions from 57 million cars.
E-waste:
AI hardware components can become obsolete quickly. This results in the disposal of electronic waste (e-waste). A study by the United Nations University found that in 2019, global e-waste generation reached a record high of 53.6 million metric tons. The report notes that the production of electronic devices and equipment, including those used for AI applications, is one of the primary drivers of e-waste.
All these grim examples are painting a bleak picture, then why is the world so driven toward AI?
Why are we spending billions of dollars on developing the next big Artificial Intelligence?
The following section will shed a brighter light on the far-reaching benefits of AI. These are perhaps reasons enough for humans to strive for improved AI models. Despite all those associated practical risks and follies.
“The greatest benefit of the arrival of artificial intelligence is that AIs will help define humanity. We need AIs to tell us who we are.” — David Hanson
“AI is the new electricity.” — Andrew Ng (Wired, 2016)
* Increased efficiency and productivity:
AI can help businesses and industries optimize their operations and achieve better results. For instance, companies like Amazon and UPS are already using AI to streamline their logistics. They are using AI to enhance delivery operations, reducing shipping times and costs.
A study conducted by Forrester Research found that AI-powered automation can save up to 20% of employee time. Which can be reinvested into high-value tasks.
* Improved decision-making:
AI systems can process and analyze vast amounts of data, allowing humans to make more informed and accurate decisions. AI can analyze data to identify patterns and correlations that humans might not be able to discern. AI-powered decision-making can increase productivity by up to 40%, according to a study by McKinsey.
* Enhanced creativity and innovation
AI can help humans come up with new ideas and solutions by analyzing and synthesizing data in novel ways. For example, AI-powered music and art can create original works that blend human and machine creativity. For example, a music composition software called Amper Music uses AI to generate original music tracks based on user preferences and inputs.
· Augmented Reality: AI can enhance the human experience by enabling the creation of immersive and interactive experiences. This can be done through augmented reality (AR). For example, AR platforms like Snapchat and Instagram use AI-powered filters to create fun and engaging visual effects that allow users to express themselves creatively.
· AI for accessibility and inclusivity: AI can help make products and services more accessible to people with disabilities, allowing them to participate fully in society. For instance, AI-powered tools like voice recognition and natural language processing can help people with visual or motor impairments interact with technology more easily.
* AI in Education
Artificial Intelligence (AI) has already begun to impact the education sector in various ways. From personalized learning to intelligent tutoring systems. In the future, AI is expected to revolutionize the way education is delivered and received.
Personalized education:
AI-powered platforms can provide personalized education and training programs. Tailored to each individual’s learning style, pace, and preferences. For example, Carnegie Learning’s AI platform provides personalized math instruction to students
Intelligent Tutoring Systems:
Carnegie Mellon University has developed an ITS (Intelligent Tutoring System) called the Cognitive Tutor. It has been shown to be effective in improving student performance in math.
* AI in Healthcare:
AI can help healthcare professionals make better decisions by analyzing patient data and identifying potential health issues. For example, researchers at Stanford University used AI to identify a drug that could potentially treat COVID-19 (Wang et al., 2020).
Diagnosis and Treatment: AI can assist in medical diagnosis and treatment. For instance, AI algorithms can analyze medical imaging scans. And identify anomalies that may be missed by human interpretation. AI can also help in identifying drug combinations that are effective in treating specific conditions (e.g., cancer). And can predict treatment outcomes based on patient data.
Predictive Analytics: AI can be used to analyze patient data and identify patients who are at risk of developing specific conditions (e.g., diabetes, heart disease). It can then recommend interventions to reduce that risk.
Precision Public Health: AI can analyze data from social media platforms and identify trends in disease outbreaks. Or predict the spread of infectious diseases.
* AI in Finance:
AI can help financial institutions make better investment decisions. It can do that by analyzing market trends, predicting risks, and detecting fraud. AI can also help in credit scoring, loan underwriting, and customer service. For example, JPMorgan Chase & Co. uses AI to analyze customer data and provide personalized investment recommendations (Noyes, 2019).
* AI-powered Smart Homes:
AI-powered devices like smart speakers and smart thermostats can learn users’ preferences. It can adjust settings accordingly, making daily tasks more convenient and efficient. AI-powered home security systems can also analyze video feeds and alert homeowners to potential threats.
Artificial General Intelligence (AGI)
It is a hypothetical form of artificial intelligence. It’s an AI capable of understanding or learning any intellectual task that a human being can. It is often contrasted with narrow AI, which is designed to perform a specific task or set of tasks. AGI is not currently prevalent, as it is still a theoretical concept.
Generative AI
It refers to a class of artificial intelligence systems that can generate new and original data, such as images, music, speech, or text, that mimic human creativity. Generative AI models use machine learning techniques, such as neural networks and deep learning. It uses ML to learn patterns from large datasets and then uses these patterns to generate new content.
One of the most advanced Generative AI models is ChatGPT (Chat Generative Pre-Trained Transformer). OpenAI, the new silicon valley sensation is the company that created this model. Only within a few months, we are seeing a sprawling number of generative AIs. As we busk in their glory, we are in fact witnessing a pathway toward AGI. And it’s already raising concerns around the world.
Currently, the most advanced AI language model, GPT-4, can perform a wide range of language-related tasks. But, it’s still limited in the ability to understand language in the same way that humans do. Whereas, An AGI language system would be able to understand the meaning of the sentence. Even if it involves subtle nuances or cultural references. While this is true, the tech report of OpenAI on GPT-4, showed some exciting yet alarming signs. They demonstrated with evidence that GPT-4 could understand the joke on an image. It completely grasped humor and explained it in detail. The report also admitted the company’s fear of subtle Singularity concerns.
Singularity: The point of no return!
I want to end this AI saga with the most debated, talked about, and controversial concept in the AI world. The concept of singularity. It refers to the hypothetical scenario in which AI surpasses human intelligence. This could lead to unforeseeable consequences, as we would no longer be in control of the technology we created. The concept was popularized by mathematician and computer scientist Vernor Vinge in the 1990s. It has been further developed and discussed by futurists, scientists, and philosophers in the years since.
Although, still a concept, a few AI incidents sparked a spooky concern amongst the people of the world. It also raised more questions than answers on the future of AI.
In 2016, Microsoft released a chatbot named Tay on Twitter. It was designed to learn from interactions with users and become more human-like. But, within hours of its release, Tay began tweeting racist and offensive messages. These included Holocaust denial and support for genocide. Microsoft shut the chatbot down and apologized for the incident.
In conclusion, the likelihood of singularity is a matter of debate and speculation. But, as it turns out, one thing is for certain, AI is here to stay. Either we adjust and evolve with it, or be a bystander long enough to see ourselves replaced. The future of this world now rests on this rivalry and co-existence between Humans and Artificial Intelligence.
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