Top Concerns & Challenges with Generative AI

While artificial intelligence isn't necessarily new, it has now become commoditized and available to everyday users. And since it's still the early days of generative AI, it's important to consider the potential concerns and challenges that it poses for you and your clients.

Kevin Dunn of HubSpot and Paul Roetzer of Marketing AI Institute recently discussed the impact and implications AI can have on process efficiencies, creativity and productivity, and more in this Agency Unfiltered episode.

And there is no doubt that technology as powerful as ChatGPT has it's potential flaws and risks. Sam Altman, CEO of OpenAI recently had this to say about this topic:

"I think if this technology goes wrong, it can go quite wrong. And we want to be vocal about that. We want to work with the government to prevent that from happening. We believe that the benefits of the tools we have deployed so far vastly outweigh the risks, but ensuring their safety is vital to our work" - Sam Altman, OpenAI

Organizations, governments and even the UN are racing to figure out what guidelines, guardrails, laws and regulations need to be in place to ensure safe use of this rapidly advancing technology. Below are a few considerations to take into account when it comes to the challenges posed by generative AI.

Data Privacy and Security

This is one of the biggest concerns at the moment, which is why it's essential to ensure that the data used by tools like ChatGPT is adequately protected from unauthorized access, theft, or misuse. This might involve implementing robust security measures such as encryption, access controls, and multi-factor authentication, among others. Additionally, data privacy regulations such as GDPR and CCPA must be followed to ensure that user data is not misused.

Trustworthiness and Accuracy

In this TechTarget article, Scott Zoldi, Chief Analytics Officer at credit scoring services company FICO, said 'ChatGPT-4 is mining the internet for data, and a lot of it is truly garbage, presenting a basic accuracy problem on answers to questions to which we don't know the answer.'

So, while ChatGPT is an excellent tool for generating text, it's still a machine learning model and can make mistakes. Therefore, it's crucial to monitor the accuracy and reliability of the output carefully. This can be done by conducting regular tests and evaluations of the system's performance, including manual reviews of the generated text.

If you haven't tuned in to HubSpot's podcast 'Marketing Against the Grain' hosted by HubSpot's CMO, then make sure you check out the below episode where they discuss the most impactful areas of AI, how it will forever change the customer experience, why AI writing tools weren’t the best place to start, and the power of personalization.

Increases in Biases

Another area to consider is the impact generative AI and language models have when it comes to increases in biases. ChatGPT generates text based on its training data, which may contain biases or inaccuracies. Therefore, it's essential to maintain transparency and explainability in the system's output. This includes providing information on the data sources used, the model's training process, and the reasoning behind the system's output.

On the flip side, tools like ChatGPT can be used to remove your own personal biases.

Pro Tip: when using tools like ChatGPT, request for it to provide the sources it is referencing in its outputs, so you can verify and confirm their accuracy and biases.

Use and Misuse of AI

It's no surprise that with the democratization of generative AI tools, everyday non-technical users can easily lead to misuse, which could potentially harm individuals, communities, and organizations. Therefore, it's vital to establish ethical guidelines and best practices to ensure that the technology is used responsibly. This involves establishing protocols to prevent misuse, monitoring and auditing the system for potential misuse, and establishing mechanisms for reporting and addressing any incidents of misuse.

AI Stealing Our Jobs

This has been one of the top reactions people are having when discussing the topic of generative AI, with them questioning if it'll kill jobs. Content creators, artists, filmmakers, creatives, and coders all share warranted concerns.

However, as we continue learning more, we're quickly seeing that these models will require a human touch at the very least, shifting people's view of these tools as 'assistants' versus 'job killers.' In 2020, MIT released this report where they concluded that AI will likely not result in massive job displacement but rather work with humans as 'superminds'.

In fact, HubSpot's new research shows that AI isn't necessarily taking any jobs away and that a majority of marketers view AI as a way to generate ideas, outlines, and first drafts, but not final published pieces of content. 

If you missed it, watch this episode of Marketing Against the Grain where HubSpot's CMO, Kipp Bodnar and Zapier's CMO, Kieran breakdown the debate around AI stealing or changing jobs.

Objections from Clients

As mentioned earlier, another challenge to watch for is client objections related to AI. We’ve provided some initial considerations on how to handle these objections in a later section.

Impact on Pricing & Services

As mentioned earlier, another challenge you may or may not face relates to pricing and services you offer. You may need to consider adapting both of these depending on how things play out. This Harvard Business Review article from 2021 discusses what professional services businesses must do to thrive in the future and it's still relevant today for what we're experiencing in the market.