At the 20th annual MozCon, Britney Mullerfounder of Data Sci 101, gave an eye-opening presentation on AI and its impact on digital marketing.
His session, “The Dark Side of AI: What Marketers Need to Know,” provided a comprehensive overview of AI’s current and future potential.
Muller discussed the ethical considerations, practical applications and limitations of AI, offering valuable advice to marketers.
The emergence of generative AI
Muller began by discussing the rise of generative AI, which sits at the intersection of AI, machine learning, deep learning, and natural language processing (NLP).
She explained:
“Generative AI, in particular, has emerged from this interesting overlap of fields.
We have AI that hosts machine learning. Within machine learning, there is deep learning. And then human language comes into play with NLP or natural language processing.
Photo taken by the author at MozCon, June 2024.A significant part of Muller’s presentation focused on the crucial role of training data in AI models.
She emphasized:
“I used to say that AI reflects its training data, and I’m going to double down. This amplifies its training data.
Muller highlighted the lack of diversity in datasets like Wikipedia, where contributors are overwhelmingly male, and how this can perpetuate bias in AI results.
Photo taken by the author at MozCon, June 2024.Practical applications and limits of AI in marketing
What Generation AI is good at
Muller presented a wide range of practical applications of AI in marketing, as one of his slides shows.
Photo taken by the author at MozCon, June 2024.She explained:
“LLMs, in general, are good at all of these things, and it is my unpopular opinion that content generation is one of their worst abilities. They are much better at sentiment analysis, labeling things as categories, providing code support.
Additionally, she shared a slide highlighting specific applications of GenAI SEO/marketing, including:
- Automatic titles and meta descriptions
- Aata Cleaning
- Coding help
- Accelerate creativity and ideation
- Personalized awareness
- Sentiment analysis
- Refurbished Content
- Chatbots
- Transcription of meeting notes
Photo taken by the author at MozCon, June 2024.How GenAI is bad
Photo taken by the author at MozCon, June 2024.Muller discussed the limitations of LLMs, who struggle to carry out tasks requiring:
- Factual accuracy
- Common sense reasoning
- Understand the context
- Dealing with unusual scenarios
- Emotional intelligence
- Mathematics/account
Marketers need to recognize these strengths and weaknesses when integrating AI into their strategies.
Quick Engineering Tips
To help marketers use generative AI, Muller provided practical tips for rapid engineering.
Photo taken by the author at MozCon, June 2024.His three suggestions were:
- Explain the task as you would to a person
- Use examples to illustrate what you want
- Give the model a “role” and tell them about the target audience
She advised:
“Explain the task or problem as you would to a person. There’s been so much research on rapid engineering, and oh, these things work, but these things don’t work. The biggest takeaway from all this research is the examples. It’s just showing the model, hey, this is good or bad, and we want the result to look like this.
Muller shared a slide of generative AI tools and resources such as Colab, Kaggle, GPT for Sheets, Ollama, WordCrafter.ai and his own DataSci101.com.
Photo taken by the author at MozCon, June 2024.Key Takeaways and the Future of AI in Marketing
Muller concluded his presentation with several key points captured in his closing slide.
Photo taken by the author at MozCon, June 2024.She highlighted the need for a people-centric approach to AI, recognizing its potential as an assistive technology rather than a total replacement for human expertise.
Key points to remember:
- GenAI is a predictive technology
- The quality of a model depends on its training data
- Marketers have the power to imagine the next brilliant GenAI application
- Show up online where the conversations about your product/service are happening
She said:
“We need to talk more about people-centered AI, right? What will be the best model to support the people we work with? And that it is a predictive technology. A model is only as good as its training data and constitutes assistive technology. It’s not a complete replacement for you, and it won’t be.
In summary
Muller’s ideas provide a valuable guide to navigating the complex world of AI.
Throughout his presentation, Muller reiterated that AI should be viewed as an assistive technology rather than a complete replacement for human expertise.
She encouraged marketers to identify tasks that AI can help speed up or automate while still retaining a human touch.
Muller’s key message to marketers is to adhere to ethical practices, prioritize human needs, and capitalize on AI’s strengths while recognizing its weaknesses.
Featured image: Abnalladin/Shutterstock
