CHATGPT: RISKS AND REWARDS OF GENERATIVE AI

Generative AI, like ChatGPT, playground AI, Midjourney, Stable Diffusion, and more have the potential to revolutionize businesses, but we must understand the risks and rewards it can create.

Physicist Richard Feynman once said, “I think I can safely say that nobody understands quantum mechanics.” Following in the same vein, it’s safe to say that nobody understands generative AI…yet.

If you’ve heard of ChatGPT, though, you’re on your way to becoming familiar with generative artificial intelligence (AI). Introduced to the public in November 2022, ChatGPT and other generative AI tools are getting plenty of global attention and quickly going mainstream, with the market projected to grow to USD 110.8 billion by 2030.

Yet, as the decade of the 2010s saw major advancements in AI, the 2020s may be the decade of reckoning when we begin to see the impact of these advancements on society. To better understand generative AI and its potential, we’ll explore what it is and what it can do, along with the risks and rewards for the connected enterprise.

WHAT ISA GENERATIVE AI?

Generative AI refers to a category of AI algorithms that generate new outputs based on the data they have been trained on. It uses a type of deep learning called generative adversarial networks and has a wide range of applications, including creating images, text, and audio.

In the case of ChatGPT or other text generators, it “learns” from text data to understand context, relevancy, and how to generate human-like

Burkhard Hilchenbach

Lead Architect, Hybrid IT, Software AG responses to questions. Instead of just replicating existing text, its generative AI algorithms identify patterns in text and then create something original.

THERE ARE THREE BASIC DIMENSIONS OF GENERATIVE AI:

Input: The First Dimension of Generative AI

The first dimension is the input—or the actual data that’s consumed—when the generative AI algorithm is inferencing. This input is predominantly text but it can include other source formats like images.

Output: The Second Dimension of Generative AI

The second dimension is the output that’s generated, such as text, images, 3-D models, music, videos, programming code, etc. The quality of the output is directly related to the size of the dataset it is trained on.

Specificity: The Third Dimension of Generative AI labor market. As economist Paul Krugman recently wrote in The New York Times: “It’s possible that in some cases, AI and automation may be able to perform certain knowledgebased tasks more efficiently than humans, potentially reducing the need for some knowledge workers.”

The War For Reality

Every day, it’s becoming harder and harder to distinguish between what’s real and what’s not. There are now serious challenges for the public in assessing reality and trusting that what they’re seeing is authentic. AI-generated text, images, and videos only exacerbate these challenges, requiring additional software that can flag AI-generated content.

WHO CREATED WHAT?

Generative Ai And The Connected World

Generative AI tools like ChatGPT are disrupting the world as we know it. There are still many unknowns about how generative AI will ultimately be used, by whom, and for what purposes. But the technology offers as much promise as it does risk. For enterprises that are seeking to create the connected experiences their employees, partners, and customers demand, generative AI has enormous potential for use in business processes and enablement of new business models. Generative AI has great potential for use in business growth and enablement, but it’s just one piece of the vast puzzle that is the connected enterprise.

The third dimension is the specificity of the output for a given domain or task. Some AI will focus on a very specific domain and the ‘answers’ they will give will be highly reliable and to the point. Examples like DoNoTPay for legal advice will quickly mature in capabilities. On the other side of the spectrum general-purpose AIs like ChatGPT.

Risks Of Platforms Like Chatgpt

From a professional standpoint, generative AI puts us on the brink of a new wave of software creativity and the seemingly limitless business solutions that can result from it.

One major concern around generative AI is the near-term effect it could have on the

The person (or machine) doing the creating can get called into question too. Last year over just over three months, more than 10 million people used the Stable Diffusion text-to-image tool for generating images.

An Existential Crisis In Education

Generative AI raises even more questions in schools and universities, in which intellectual achievement is dependent on the student’s thoughts, research, and writing. Though derived from existing content, AI-generated content is essentially original.

Ai In The Hands Of Malicious Actors

In the wrong hands, generative AI can be used for truly nefarious reasons. Malicious actors can use it to create everything from propaganda to phishing emails and malware, to fake websites and businesses, to text that’s meant to impersonate someone. It can even be used to create new forms of warfare and weapons. n