The market for artificially intelligent software is growing exponentially and will reach almost $134 billion by 2025. AI, at its core, is a field of computer science that simulates human intelligence through algorithms and models, enabling computers to perform tasks that typically require human intellect. While it offers immense benefits, it also poses significant challenges and risks that warrant careful consideration.
Understanding the types of AI
· Machine learning (ML) algorithms and techniques allow systems to make decisions from data without being given exact directions. For example, ChatGPT uses machine learning to respond to prompts from humans. Deep learning is a subset of ML that uses models, called neural networks, inspired by the human brain, to do more advanced tasks.
· Narrow AI, also called weak AI, is focused on doing just one task, rather than simulating human thinking. Examples include voice assistants, chatbots, image recognition systems, self-driving vehicles, and maintenance models.
· Generative AI. Unlike weak AI, generative AI refers to the creation of new content, such as images, text, audio, and videos. Models are trained to see patterns in data, and, using that learning, generate original content that is similar – but not the same – as the original data. Generative adversarial networks (GANs) are made of two neural networks: a generator network and a discriminator network. The generator network creates new content, while the discriminator network differentiates between the generated content and real content. This form of AI, which is growing in popularity, has a positive impact on society through apps like Supertone, Imagine and Jitter.
But like with other forms of AI, there are concerns about misuse and negative consequences. It is worth examining some of these concerns.
1. AI exposes companies to plagiarism and copyright infringement
AI technology can generate content and images based on training data, so results are never totally original. Without meaning to, this can duplicate fictional works, business plans or works of art that would fall into an official definition of plagiarism. Likewise, AI images, audio and video generators expose users to copyright infringement. Since AI mines things like internet content, audio clips from social media, and videos, these tools often use material without official permission, exposing companies to lawsuits.
2. Cyber-attacks can be optimized and malware automated
Attackers can use generative AI to find new ways to undermine cloud complexity and launch complex strikes, including ransomware and phishing attacks. They can also use AI apps like ChatGPT to code malware more effectively. AI-powered tools may make it possible to create automated malware, like an advanced malicious bot, which can steal data, infect networks, and attack systems.
3. Data manipulation and data poisoning
Since AI is dependent on training data, it opens the door to data manipulation. If the data is modified, an AI-powered tool can produce unexpected or even catastrophic results. It just takes one bad actor or even a mistake in data input to compromise trust in a business when AI – without sufficient human oversight—is in charge.
4. Privacy Risks
You may have heard that ChatGPT leaked the chat history of users. Although the bug was fixed, there are other possible privacy risks due to the large amount of data AI crunches. As with other new digital tools, some have concerns about privacy, specifically that the company records every conversation to improve the chatbot. In fact, even after you delete a chat from the sidebar, a copy will continue to exist in a de-identified form.
With the right footage, anyone can make deep fake footage or realistic voices by using free apps. A particularly scary example of this capability is AI kidnapping schemes. Jennifer DeStefano received a call from her daughter in distress. Then, her voice was replaced by that of a man who threatened to drug and abuse her daughter unless paid a $1 million ransom. We now know that the voice was generated by AI. As anyone who has tried ChatGPT knows, it is also possible to generate text in various styles. These can be used to create scams such fake investment opportunities, social media posts that misrepresent the thoughts of a real person, and even faulty and misleading scientific research.
6. Physical safety may be compromised
We do not usually think about physical risks when we consider AI, but when vehicles, appliances and drones are programmed using AI, there is the possibility of physical mishaps. For example, a drone that is programmed to hit a target might do so at the expense of people in its way. A small error in the code could lead to injury or even death.
How to prevent AI dangers?
1. Checking the reputation of any AI system you use can help avoid security and privacy issues. Do not share confidential information on artificial intelligence. To protect AI from data poisoning, companies should also invest in encryption, access control, and backup technology. Secure networks with firewalls, intrusion detection systems, and sophisticated passwords.
2. It is also important to update AI software, operating systems, and apps with the latest updates to reduce the risk of exploitation. Use the latest antivirus technology, network, and application security to stop advanced threats.
3. Train AI to respond to attacks. The more it is exposed to attack scenarios, the more it can build up resilience to threats. Consult with experts in cyber security and AI to train yourself or your employees in AI risk management. For example, we should all learn to discern which emails may potentially be phishing attacks designed by AI. Likewise, we should avoid opening unsolicited software that could be malware.
AI holds transformative potential across various domains, but its rapid advancement necessitates thoughtful navigation of its complexities. By fostering responsible AI development, embracing ethical practices, and staying informed about evolving risks, we can harness AI’s benefits while mitigating its challenges.