While AI technology has increased applications by a staggering 300% in the last decade, it moved from simple chatbots to complex conversational AI understanding human language patterns amazingly. People wonder if it is really safe to converse with artificial intelligence for normal day-to-day conversations or sensitive queries. They also said that while AI can process and analyze information at speeds up to 5,000 words in one second, it is much contextual and purpose-related. Companies like IBM-Watson have proven in various applications, including customer service, that AI can handle up to 80% of normal queries without human interference. Safety here is ensured through encryption protocols and adherence to the laws on data privacy, such as GDPR in Europe. However, the use of even giant AI systems by Amazon and Google collects and analyzes great quantities of personal data-nearly 2 billion data points from conversations alone each year, which would be a substantial risk if unregulated or accessed by unauthorized parties.
AI will give a productivity boost for personal use: some users can save up to 40% of their time, as mentioned earlier, by doing repetitive tasks. Greater efficiency brings along the risk of "data permanence." When anonymized information enters an AI model, the studies from Stanford University have shown it can stay in training data for years. The permanence of data retention and the possibility of its misuse—particular in situations where algorithms can be susceptible to "data leakage"—makes it important that users understand the implications of what they reveal when they speak to AI.
One issue is lack of privacy. Recently, for instance, companies like Microsoft and OpenAI have begun offering AI tools designed for industries that require particularly high levels of privacy, such as healthcare. Because their AI tools are designed to process sensitive patient data under strict HIPAA compliance, this alone raises the bar for data protection. No AI system-even with all these-is completely breach-proof. In 2020 alone, the average cost of a data breach to companies was $3.86 million per incident. The question isn't one of the capability of AI, but rather its deployment: Is the AI system so designed as to deploy the necessary safeguards that protect user information?
There is also a concern about the complexity of AI decision-making. While human conversations are very unique to the individuals involved, AI responses emit from very large datasets that may or may not be representative in specific needs. As the philosopher and cognitive scientist Daniel Dennett once said, "AI systems are only as unbiased as the data they're trained on." That is to say, users continue to run the risk that AI-which has, after all, been developed through and informed by prior conversations and interactions-will promote biases rather than provide impartial, clear guidance.
It would be necessary to consider that safety needs to be evaluated based on intent. More suitably put, one can say that AI systems developed by companies like Google DeepMind or OpenAI's ChatGPT are meant to be specifically restricted from being able to do a lot of bad things in the first place. For example, they will not make posts that will lead others to commit illegal activities, hate speech, or fake news. While these restrictions are strong, responsibility in using AI must come from users themselves, along with making them more aware of policies on platforms.
For anyone seeking to interact safely with AI, the said factors that need to be understood are data security, limitations in the system, and safeguards against sinister intents. talk to ai for more insights on this topic.