By Nisha Sharma - February 03, 2023 5 Mins Read
Without a human-centric approach, OpenAI ChatGPT runs on the data available on the various channels, which can also deliver services without meeting the context requirements. Sometimes, it writes plausible-sounding content but can be trustworthy.
The new kid on the block, AI-powered ChatGPT offers numerous exceptional services and is claimed to be useful for coding, content writing, etc., minimizing human intervention. As erudite machinery becomes a trending sensation, companies can also see AI biases, security risks, and less personalized CX.
The uncapped accessibility, and unrestricted usage of ChatGPT have increased the cybersecurity risks that can hamper the whole organization. Through ChatGPT, cybercriminals can draft a fraudulent email carrying unsecured links, attachments providing sensitive data, or instructions regarding transferring money into specific accounts from a reputed company or person. Because of available data in ChatGPT, the incidents of phishing emails will increase.
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Guy Hanson, VP of customer engagement at Validity, says– “We’ve already seen many examples of ChatGPT being asked to create content using the style and tone of voice of a specific person. Spear-phishing targets individuals or organizations, typically through malicious emails, by attempting to mimic someone with whom they already have a trust-based relationship.”
Other than this, the ChatGPT will fail to secure customer or company data from any malware and can cause ransomware attacks, increasing the probability of data theft. It can be turned into a diabolical arsenal of cyber lances waiting to be stolen.
ChatGPT has limits when creating a practical conversational AI system. It’s important to understand where the boundaries are drawn in order to create a conversational AI system that doesn’t give the incorrect answer, isn’t overly biased, and doesn’t keep people waiting for too long. Using these technologies to create a custom conversational AI system involves several tradeoffs. The closed, end-to-end structure of ChatGPT and GPT-3.5 prevents engineers from experimenting with them, even though they can offer compelling answers to queries. That also poses a challenge when trying to produce the response from a unique corpus of words for a particular sector (retailers and manufacturers use different words than law firms and governments). Additionally, its closed nature makes bias mitigation more challenging.
Search engines often fail to understand the context. Users frequently need to actively click on several links, read the content, and decide whether it fulfills their search goal. However, it also means that users are aware of the precise of source information and whether it is credible.
On the other hand, ChatGPT can comprehend the question’s intent and deliver a detailed response that is typically relevant due to its underlying language processing skills. However, ChatGPT does not include any references or links to the data it presents.
“There is definitely ambiguity as to whether AI using its training from billions of other sources, can be classed as original content. There is already a California lawsuit based on copyright infringement by AI models that have been trained on billions of images from the web without consent.”- says Hanson.
When there is repetition in any content creation tool, it will be like kryptonite using artificial intelligence and machine learning, and ChatGPT is the same. ChatGPT is excellent; it produces good content but does not use the internet and works on an AI-based, unlike other AI assistants. It creates content word by word and chooses the most likely word that must come next as per its training. The content produced by ChatGPT can have different contexts which are not preferred by the users, as it writes by making a series of guesses which cannot be wholly accurate or cannot be satisfying for the users.
“Commentators are overlooking that ChatGPT is still in beta, with OpenAI using all the learnings from this test to create a more robust solution that will be made available for commercial use. What’s impressive is that (so far, at least) it has avoided the bias that quickly developed in previous solutions, such as Microsoft’s “Tay” chatbot, which became right-wing, racist, and homophobic within 24 hours of release, “says Hanson.
ChatGPT can reduce human efforts but replacing them will take much work. Every business focuses on providing personalized customer experience to the buyers, which can be maximized with a human-centric approach. ChatGPT can be a powerful learning tool, but companies can rely on it blindly.
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In a few years, companies will see how AI will determine the network, layout, and architecture and then manipulate the toolchain to obfuscate payloads to avoid detection by defenders. If companies leverage ChatGPT in all their operations, there will be no one to monitor whether the processes lead in the right direction.
Emmanuel Walckenaer, CEO at Yseop, says,“Today, enterprises are expected to process incredible amounts of data, but many struggles to find the best ways to organize and make sense of it all, which has resulted in wasted time and money. It has also created inefficient employees who are susceptible to burnout because humans were never meant to process this much data at once, and there are often countless errors and mistakes throughout human reporting.”
Despite many benefits, AI-powered ChatGPT is not risk-free to depend on. It can be helpful but not fully reliable for business operations.
Emmanuel suggested- “This year, companies should reassess what is important to the overall organization, which could be leaving data analysis and reporting up to more efficient, AI-enabled technologies to allow employees to focus on strategic decision-making and more creative projects.”
Because of the absence of human interventions, companies will see the detection of vulnerabilities, weaponization of cybersecurity threats, and payloads all done by AI.
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Nisha Sharma- Go beyond facts.Tech Journalist at OnDot Media, Nisha Sharma, helps businesses with her content expertise in technology to enable their business strategy and improve performance.With 3+ years of experience and expertise in content writing, content management, intranets, marketing technologies, and customer experience, Nisha has put her hands on content strategy and social media marketing. She has also worked for the News industry. She has worked for an Art-tech company and has explored the B2B industry as well. Her writings are on business management, business transformation initiatives, and enterprise technology.With her background crossing technology, emergent business trends, and internal and external communications, Nisha focuses on working with OnDot on its publication to bridge leadership, business process, and technology acquisition and adoption.Nisha has done post-graduation in journalism and possesses a sharp eye for journalistic precision as well as strong conversational skills. In order to give her readers the most current and insightful content possible, she incorporates her in-depth industry expertise into every article she writes.
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