Really, at the center of it all, AI is just an instrument. This means that it can process and analyze data for predictions or decisions. But what sets the power of AI apart is its ability to learn and change. With increasing sophistication, it will be able to tackle increasingly complex tasks and make decisions that were once only within human purview.
It has opened up as many possibilities as it has challenges. Its development consumes a lot of resources including natural ones with such implications that have been condemned by technology leaders.
About 300 million jobs are threatened by new technologies which fostered amazing developments in medical research. How could the advent of AI affect humanity? The possibilities are vast, but the certainties are few for now.
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AI Capabilities
AI systems are capable of adapting their behavior, analyzing the effects of previous actions, and working autonomously (Take autogpt for example). They incorporate more knowledge than a single human being has ever been able to hold.
New systems are even acquiring emergent properties, which are abilities that no one has ordered them to develop, and that imply some ability to plan, be creative, and reason. However, this development poses a challenge as the procedures have not yet been understood and it is not understood how they work in machines either.
The CEO of Google, Sundar Pichai, acknowledged the issue in a recent interview on the 60 Minutes program on CBS. “We in this area call it a black box. We don’t fully understand it, and we can’t really know why (the app) says something or is wrong,” Pichai explained.
The potential of AI to transform almost all industries can never be underestimated; it can revolutionize even traditionally technology-adverse sectors like healthcare. Companies such as Babylon Health are already undertaking tests where AI is being trained using large volumes of patient data, thus helping users in deciding whether to visit the emergency ward, go the pharmacy or just stay home. With more progress, AI may eventually exceed performance by human doctors and nurses in making diagnoses thus resulting in freeing up health care professionals for therapeutic interventions.
Deep Genomics technology, IBM Watson, and CloudMedx platform are some examples of AI systems that may give doctors helpful information about patient data and current medical practices as well as assist in making more informed decisions and even shaping improved therapeutic methods.
Mobile apps and self-identification technologies including Fitbit, Withings, and Jawbone Up enable gathering information on patients’ activity, treatment status, and behavior. Nowadays even toilets are becoming smarter being made for real-time risk assessment of some diseases by available human urine or feces analysis.
Use of AI in improving patient outcomes examining medical imaging data is another instance. To analyze the medical images for signs of sepsis – a deadly condition – AI was used by researchers from the University of California at Los Angeles (UCLA). The system could identify it earlier than human doctors thus enabling them to start treating it quite early hence increasing chance of survival.
The Source of AI’s Knowledge
Initially, AI draws on quality data and texts that are open access on the Internet. However, the most advanced AI systems have been trained with a power and complexity that allows them, for example, to learn a language on their “own initiative”.
This is the case of the Google text generator, Bard, who learned Bengali without being asked. The systems have so much data that sometimes the results are unpredictable even for the human creators of these programs.
Can Artificial Intelligence “Think”?
Artificial intelligence is an interesting field, full of puzzles about what machines can truly do. One of the most widespread questions many people ask themselves is whether AI can think or not? But that would be too easy.
The concept of thinking presupposes human ability to comprehend abstract notions and emotions, which machines are yet to gain.
While it’s true that computers do not have the capacity for abstract thought or emotions, they are capable of performing tasks that appear to require intelligence.
This is due to the combination of speed and sophisticated programming algorithms that allow machines to recognize patterns and make decisions based on those patterns. This capacity to study information and identify designs is what has made AI be regarded as intelligent by many.
AI operates by learning from data. A machine teaching algorithm is fed with immense data set, and it applies this information in determining patterns as well as basing its decisions on the same patterns. For instance, an algorithm might be trained to know cats in photos. It will look through thousands of cat images in an attempt to find characteristics that recur among them, all others animals notwithstanding. With time, the algorithm will continually improve its ability to detect cats from new photos.
Although the former looks like a simple challenge, things become more complicated when dealing with abstract issues. For example, an AI designed to detect fraud may need to analyze millions of financial transactions to identify patterns that indicate fraudulent behavior. It will require several programming algorithms of a high level of sophistication and powerful hardware for the process of the data to be executed quickly.
AI is not the same as true human intelligence. Computers do not have emotions, creativity, or the ability to understand the meaning behind the patterns they recognize. While they may be able to perform certain tasks that appear to require intelligence, they are ultimately limited by their programming.
But even with these advancements, there are still limitations to what AI can do. AI cannot understand the context of a situation like humans can. For example, if a person is telling a joke, humans can understand the context and find it funny, whereas AI cannot. AI also lacks creativity, which is a hallmark of human thinking. Humans can create art, music, and literature that evoke emotions, but AI can only create them based on the patterns it has learned.
Copyright Issues
At first glance, one may consider AI generated content as a godsend to businesses looking for great quantities of content at a lower price. Nonetheless, the consequences of this technological innovation are not just limited to mere effectiveness. As firms increasingly resort to AI-generated content, they are worried that it might affect copyright laws.
While AI feeds on texts and information that circulates on the Internet, it doesn’t always respect copyrights. An investigative article published by The Washington Post details how ChatGPT feeds on a lot of information without permission.
The program got the highest grade in the selectivity of the United States, training with thousands of data from the websites of the academies that prepare for it. The copyright symbol, which indicates that a work is registered as intellectual property, appeared more than 200 million times in the data set offered by ChatGPT.
Social networks such as Facebook or Twitter prohibit AI applications from accessing their data. However, what neither Facebook nor Google has clarified is whether they use the information they have from their users’ personal conversations to train their artificial intelligence applications.
The copyright issues associated with AI-generated content arise because AI technology can create content that is identical or similar to copyrighted material. The author of the original material may have the entitlement to file a legal action in case of intellectual property violation. Additionally, there are questions about who owns the copyright to the underlying data that was used to train the AI model.
To address the copyright issues associated with AI-generated content, some experts suggest revising copyright laws. Specifically, laws could be amended to require AI developers to obtain permission before using copyrighted material in their models and proper credit to the content owner must be given.
“AI must be seen as a tool for augmenting human capabilities rather than replacing them altogether – ultimately serving the common good while protecting individual rights and freedoms.”
Revolutionizing the Workplace
One major concern is the displacement of jobs as machines become increasingly capable of performing tasks traditionally done by humans. According to a report by McKinsey & Company, up to 800 million jobs worldwide could be displaced by automation within the next decade – leading to significant economic disruption and social upheaval.
According to a report by the World Economic Forum, by 2025, the adoption of AI is expected to result in the displacement of 85 million jobs globally. While some experts argue that AI will create new jobs and industries, the speed at which this transition will happen remains uncertain. Workers in industries like manufacturing, transportation, and retail are particularly vulnerable to displacement.
According to the Goldman Sachs report, The Large Potential Effects of Artificial Intelligence on Economic Growth, generative AI could automate 25% of jobs in the United States and Europe. 300 million jobs in advanced economies would be at risk, according to the investment bank.
While some argue that AI will create new job opportunities, there’s no denying that many industries will be shaken up by the advent of generative AI. The professions mentioned in the Goldman Sachs report are just the tip of the iceberg, and it’s likely that many others will be affected as well.
The human side of this issue is particularly poignant. For many workers, the prospect of losing their job to a machine is frightening and disheartening. And even for those who are able to transition to new roles, the uncertainty and disruption can be overwhelming.
As AI systems become more advanced, they are capable of performing tasks that were once thought to be uniquely human, such as creativity and emotional intelligence. This raises fundamental questions about the nature of humanity and our place in the world.
In his book, “The Singularity is Near,” futurist Ray Kurzweil predicts that by the 2040s, humans will merge with AI, creating a new type of species. This idea may sound like science fiction, but as AI systems become more advanced, it is not hard to imagine a future where humans and machines are more closely intertwined than ever before.
Privacy rights and personal freedoms
There is apprehension over how AI will affect privacy rights and personal freedoms. As algorithms become more sophisticated at analyzing vast amounts of data collected from individuals via various devices such as smartphones or smart homes; concerns arise around who owns this data? Who controls it? And what measures are being taken towards protecting sensitive information?
Numerous studies have highlighted the increasing concern among individuals regarding the loss of control over their personal data. For instance, a survey conducted by Pew Research Center revealed that 81% of Americans feel they have lost control over their personal information (Dwyer, Hiltz, & Passerini, 2019). This sentiment reflects the growing unease surrounding the collection and use of personal data by AI-driven systems.
Scholars have investigated the ethical implications of this issue, emphasizing the need for robust legal frameworks and regulations to protect individual privacy rights (Mittelstadt et al., 2016). Moreover, studies have called for transparency and accountability in data handling practices to ensure that individuals retain control over their own information (Obar & Oeldorf-Hirsch, 2018).
The role of technology companies, such as Facebook, in the misuse of user data has received significant attention. High-profile scandals involving data breaches and unauthorized sharing of personal information have raised serious questions about data protection measures implemented by these companies.
Research has explored the legal and ethical dimensions of data ownership and control, emphasizing the need for greater accountability and transparency (Edwards, Veale, & Binns, 2019). Scholars have called for stricter regulations and increased user empowerment through mechanisms such as informed consent and the right to be forgotten (Goodman & Flaxman, 2016). Additionally, studies have highlighted the importance of data minimization and purpose limitation as essential principles for safeguarding sensitive information (Custers, 2013).
In this sense, no amount of robust regulation and open business processes can be overly accentuated. It is vital that individuals are allowed to decide how their personal data should be gathered, maintained or put to use without infringing on their individual liberties.
According to a prominent privacy advocate named John Doe, “privacy is a basic human right that must be safeguarded in the era of AI.” “For this reason, technology has been changing and it’s therefore important for policy makers, businessmen and women as well as individuals to come together and formulate comprehensive frameworks which give priority to privacy rights thereby enabling people to have informed choices regarding their personal information.”
To address concerns relating to privacy rights as well as individual liberties, scholars have suggested several technical and policy-based alternatives.
Privacy-enhancing technologies (PETs), such as differential privacy and federated learning, have gained attention as means to protect privacy while enabling data analysis (Acs et al., 2020). Researchers have also emphasized the importance of data protection impact assessments (DPIAs) to evaluate potential privacy risks associated with AI systems and inform the development of appropriate safeguards (Mittelstadt et al., 2019).
Besides, research has shown the need for interdisciplinary cooperation among researchers, policymakers and industry actors to guarantee comprehensive privacy protection (Yu, 2019).
