OpenAI’s artificial intelligence breakthrough, ChatGPT, presents improvements in retail marketing as well as in solutions for improving customer experience.
Launched by OpenAI in November 2022 as a prototype, ChatGPT — or Chat Generative Pre-trained Transformer — has become increasingly popular across multiple industries. Recent releases of its chatbox, built on the GPT Family of Large Language Models (LLM), deliver detailed responses and articulate answers in many knowledge domains.
Users can quickly create content using Generative Artificial Intelligence’s futuristic capabilities. This approach will also bring new tools for optimizing e-commerce campaigns and marketing.
Harry Folloder is the chief digital officer of CX Solutions, and he says that Harry’s use cases, both present and future, are not only interesting but can help customers deliver on their promises. Alorica. It is designed to find the best answer possible by layering generative AI on top and within other tool sets. This allows it to deliver services much faster.
“Generative artificial intelligence is a completely new game. Using these large language models, context can be created uniquely for each [human] “Interaction”, he told CRM buyer.
Although it is still unclear whether using generative AI to counter potential programming abuses or ChatGPT inaccuracies can be achieved, there are some benefits.
Can guardrails stop AI’s machine-learning (ML) and LLM, based on NLP (natural language processing), from running amok
Upgraded Features Pose Abuse Threat
The business community is eagerly anticipating the solutions that will be offered by efforts to improve CX capabilities. Experts warn that generative AI can harm brands’ reputations if it is not checked. Folloder agrees that AI should have guardrails to limit its capabilities and prevent it from going haywire.
This nagging concern is centered around the question: Can Generative AI meet Turing’s test of human intelligence in computer systems?
AI implementations in the past were largely limited to pre-trained sequences. AI was limited to what it had been programmed to perform. Generative artificial intelligence, on the contrary, can create artifacts that are of human-quality at scale. This includes fake and misleading visual, audio and written content.
A long-established method of measuring AI programs may be able to prevent AI networks from “freethinking” without being checked. The Turing test was developed in 1950 by Alan M. Turing. It is a simple measure to assess a computer’s capability to think like a human.
AI-enhanced computer systems must be able to converse with humans without being recognized as machines in order to pass the Turing test. Turing is still a long way off.
This threshold may be around the next corner.
The Thing to Look Out For Is Curation Accuracy
CX experts’ primary goal is to give customers accurate answers, reduce their frustration and improve their overall experience. Folloder highlights that AI-driven CX has the ultimate aim of solving problems more effectively, and strengthening brand protection.
This new technology is capable of exploring all sources of information without restriction. Search limits are removed, giving generative AI unlimited access and a richer integration process.
“At the speed compute, you can spread that information or something else that appears harmless on the surface. He warned that it could damage the brand in real life.
Folloder believes that when it comes to curating the content for an AI platform, clients must be protected. Folloder thinks this is one of the most important questions that are not being answered.
Imagine giving an application the ability to search all of the content on the Internet. He said that depending on how we use the tool, you can either fence off content or not. The ability of generative AI, which is on the horizon, to surpass the computer intelligence boundaries is key to this discussion.
Enter the Turing Test
The Turing test can be used to control the situation. Its history is important to the discussion.
Turing, while at the University of Manchester wrote a paper describing his thought experiment entitled “The Imitation Game.” He predicted that a computer could play the “Imitation Game” so well in 2000 that an average interrogator would not have a greater than 70% chance of making a correct identification after five minutes.
Turing’s 1939 work helped British intelligence agency MI6 break German codes including the notorious Enigma Machine. The Imitation Game (2014), loosely based off the biography “Alan Turing The Enigma” written by Andrew Hodges in 1983, depicts those efforts.
Ongoing rapid advancements in AI are raising alarm bells globally about the need to build safeguards, whether for business use cases or beyond — as discussed in April on TechNewsWorld’s The AI Revolution Is at a Tipping Point.
We are still seeing limitations in technology. How long before software developers implement guardrails to stop these limitations? Folloder interjected.
Some consumers will test the limits of generative AI as more engage with brands that integrate it. Turing remains a difficult threshold to cross for Generative Artificial Intelligence.
What are the potential and pitfalls of GenAI?
Folloder was asked to explain the need for AI advances in areas such as emotional intelligence, contextual understanding and decision making. He was also asked to share his knowledge on how generative AI is able to meet the needs for complex customer interactions while not exceeding safety boundaries.
CRM Buyer: Do You think that generative AI will ever pass the Turing Test?
Harry Folloder It is still possible to tell that the machine is not human by simply asking it a logic question. It can now use LLM to have a more humanistic conversation.
What is your deciding factor for safety concerns regarding generative AI technology?
Folloder: Today, the logic is still lacking. It is still easy to confuse and fool it. On different social media platforms, there are a ton of videos showing how easily you can mislead AI programs into writing malicious codes for you or saying things against their programmed ethical code.
What is your opinion on the possibility that generative AI can do no harm?
Folloder: I spent several years in the United States intelligence community, focusing on developing cyber practices and building the SATCOM system for the White House. So I’m not the best person to ask this question because I see it everywhere.
This tool has already been shown to be malicious. Cyber terrorists have used this AI tool’s power to improve their malware to create keyloggers with the ability to bypass today’s safety features.
What is needed to make AI more safe?
Folloder: This is the question that matters! There are no good answers to this question today. I believe a multi-billion dollar business will be built around it. We can’t keep up with how fast AI is expanding.
Do you think there is much that can be done to stop its use, like certain European countries have done already?
Folloder: I don’t think I have the best answer yet. I’m conflicted, because this is an amazing technology that should be used and propagated for the greater good. They are not mistaken in their fears. If this technology is not monitored properly, it has the potential to cause a lot more harm.
