In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the important issue of who owns your data. They talk about why companies need to be aware of who has access to their data, especially when using tools like Google Analytics or generative AI models. Katie and Chris explain how you may be giving competitors access to your data indirectly through models trained on your data. They offer suggestions for ensuring you maintain control and ownership of sensitive company data when leveraging new technologies like AI. Tune in to hear their examples and recommendations for governance, collaboration, and setting up the right data architecture.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how CEOs should approach understanding and using large language models and AI, starting with identifying business problems first before considering technology solutions.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to mitigate gender bias in AI systems by assessing risk, implementing human review processes, and building an equitable company culture.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to leverage large language models like ChatGPT with your business analytics data. We talk through real examples of using AI to analyze CRM data for buyer personas, extract tables from PDFs, summarize PowerPoints into executive briefs, transform your data into actionable insights, classify social media comments, and answer questions about your data. We explain that while generative AI is exciting, your analytics data should still be the backbone of business decisions. Tune in to learn creative ways analytics and AI can work together to enhance your marketing strategy.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how large language models with perfect memory can assist with competitive analysis. They explain how these tools can quickly synthesize vast amounts of public data to provide insights into competitors' offerings, differentiation, and performance. Katie and Chris note the importance of keeping your own data fresh so tools have current info. They give examples of how to leverage these models, from summarizing competitors' businesses to analyzing website design and content. Katie and Chris emphasize combining machine learning with human expertise to ask the right questions. They advise using AI for competitive analysis as one more tool, along with classic techniques like regression analysis.

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In this episode of In-Ear Insights, Katie and Chris discuss how to pick the right AI tools. We explain starting with the problem, not the tool. Katie recommends the 5 P's to evaluate AI readiness. We emphasize choosing AI intentionally, testing tools against requirements.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss takeaways from the recent Marketing AI Conference, MAICON 2023. We talk about the growth of the event, Chris's generative AI keynote, and share highlights from other speakers on AI regulation, ethics, and impact on jobs. We debate whether agile development processes are still needed with AI. Katie challenges the idea that QA processes can be fully automated. We speculate on an artisanal future where automation and human craft co-exist. Join us for a lively discussion on where AI is taking marketing and business.

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Since its release in November 2022, ChatGPT has been lauded as a groundbreaking AI chatbot. However, recent research indicates its capabilities may be declining over time.

In this episode of the Trust Insights podcast In-Ear Insights, hosts Christopher Penn and Katie Robbert discuss findings that ChatGPT appears to be getting worse at certain tasks it previously handled well. This includes mathematical reasoning, code generation, and visual puzzles.

There is speculation that the declines are due to OpenAI opening up access to ChatGPT's premium GPT-4 model, which overwhelmed their systems. The increased demand likely required reducing capabilities to manage traffic.

Whatever the cause, the changes have big implications for businesses relying on ChatGPT's API in their products and services. When the AI model drifts substantially in just a few months, it can break assumptions made during development.

Penn and Robbert emphasize the importance of clearly defining your purpose and requirements for implementing AI. Is convenience more important or reliability? What happens if the system goes down or its capabilities change?

For mission-critical uses, they recommend exploring open source AI models you can run on your own servers. This provides more control and avoids being subject to vendors altering public APIs.

The key takeaway is to carefully weigh the tradeoffs and have backup plans in place when utilizing third-party AI services. Model drift may not matter for minor uses but could seriously impact products dependent on certain functionality. Do your due diligence upfront to prevent disruptive surprises down the road.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to help team members stay focused on important work instead of workplace drama. They share tactics for setting boundaries as a manager, redirecting conversations, and keeping teams productive. Tune in to learn how to acknowledge emotions while maintaining priorities and guardrails.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the latest buzz in the social media marketing sphere: Threads. Threads, formerly known as Facebook Metas, is a Twitter clone built on the Instagram database and architecture. It has experienced rapid growth, surpassing 100 million users in just a few days. Katie shares her frustration with Threads being tied to Instagram, as she treats her Instagram account differently from her Twitter account. The conversation revolves around the reasons behind Threads' success, including its ease of use and the ability to import Instagram networks. Chris explains the concept of proximity of power, which Threads aims to replicate by providing users with the perception of being in close contact with influential figures. The discussion delves into the similarities and differences between Threads and Twitter, highlighting the lack of features such as desktop access, APIs, analytics, and advertising on Threads. Chris advises taking a cautious approach, maintaining both company and personal profiles, and cross-promoting Threads on Twitter. They also emphasize the importance of data privacy and being aware of the data being collected by Meta. The episode concludes with a reminder to experiment, track data effectively, and prioritize platforms that you own or have more control over.

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