INBOX INSIGHTS, December 4, 2024: Securing Our Digital Ghosts, AI Use Cases - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: Securing Our Digital Ghosts, AI Use Cases (12/4) :: View in browser

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Securing Our Digital Ghosts

The concept of a “digital ghost” has been on my mind lately, sparked by a recent conversation with Chris Penn. For those unfamiliar, your digital ghost is the collection of your work—emails, content, call transcripts—that lingers on long after you’ve left a company. In the age of generative AI, this ghost could theoretically be reanimated, mimicking your work style and processes to create value for the company, without you being there.

Let’s be clear: this isn’t science fiction. It’s very much possible. As Chris pointed out, a skilled AI practitioner could use your digital ghost to replicate how you worked when you were there. This reality raises tough questions about governance, ethics, and employee rights. What are we doing as companies, as employees, and as an industry to ensure these technologies are used responsibly?

The Ethical Challenge of Digital Ghosts

The issue isn’t just that digital ghosts exist—it’s that they can be exploited. Under typical “work-for-hire” agreements, anything you create for a company is owned by them. This means they could potentially train AI on your work and continue benefiting from it indefinitely, long after you’ve moved on.

This hits at the core of something I value deeply: treating people with respect and fairness. It’s one thing for a company to retain your work as part of its knowledge base; it’s another entirely for that work to be repurposed by AI without your knowledge or consent.

The bigger issue, as Chris rightly noted, is that companies need strong governance and retention policies to even manage this kind of data responsibly. Yet, in many organizations, these systems don’t exist or are woefully inadequate. Without them, we risk falling into the trap of using AI as a shortcut—exploiting digital ghosts instead of valuing the living, breathing people who bring real innovation to the table.

How We Can Do Better

As I reflected on this conversation, it became clear that addressing these challenges systematically is non-negotiable. This is where the 5P Framework—Purpose, People, Process, Platform, and Performance—can be especially helpful:

Purpose: Why are we retaining this data, and how do we plan to use it? Companies need clear policies that define permissible uses of data and align with ethical standards.
People: Who has a say in these decisions? Employees should be part of the conversation about how their work is used, even after they leave.
Process: How are we managing this data? Strong processes ensure that data is handled responsibly and transparently, reducing the risk of misuse.
Platform: What tools are we using? Platforms should prioritize security and accountability, ensuring that data is used only as intended.
Performance: How do we measure success? Governance isn’t a one-and-done task—it requires regular audits to ensure that policies are being followed.

Using this framework, companies can evaluate their current practices and identify gaps. For example, do you have retention policies that clearly outline what happens to employee-created data? Do your contracts include clauses about training AI on this data after an employee leaves? These are the kinds of questions organizations need to start asking—right now.

Lessons from Experience

One of the recurring themes in my career has been the need for strong governance and process development to prevent problems like this from spiraling out of control. It’s not always easy, and it’s rarely quick, but the work pays off.

For example, when I’ve helped organizations evaluate their data practices, we often start with what’s already in place. Do they know where their data lives? Who owns it? How it’s being used? From there, it’s about building workflows that ensure transparency and accountability. These processes aren’t about controlling employees—they’re about building trust, which is ultimately better for everyone.

It’s also worth emphasizing the human element here. Generative AI and digital ghosts challenge us to think about what makes our work unique. AI can replicate patterns, but it can’t replace creativity, experience, or judgment. By investing in governance and ensuring ethical AI use, we’re not just protecting data—we’re preserving the value of human contribution.

What Comes Next

The conversation about digital ghosts isn’t going away, and it’s one we all need to engage with, whether we’re business leaders, employees, or somewhere in between. If you’re part of an organization, now is the time to start asking hard questions about your policies and practices. Are you thinking about the long-term implications of how AI is trained on your data? Do you have a plan for managing employee-created content responsibly?

And if you’re an individual, it’s worth considering what rights you might want to protect in your contracts. This is still a relatively new area, but the decisions we make today will shape how we work with AI in the future.

We’re all navigating this space together, and there’s no single right answer. But by taking a thoughtful, intentional approach—whether through frameworks like the 5Ps or simply asking more “why” questions—we can chart a path forward that balances innovation with integrity. Let’s keep this conversation going, and let’s commit to doing better.

Let’s Take the Next Step Together

Since we’re now full throttle getting things done for the end of the year and 2025 planning, let’s collaborate. I want you to succeed, and Trust Insights can help! The reality of digital ghosts is a wake-up call, and it’s not something to tackle alone. Whether you’re evaluating your current governance practices or looking to build them from scratch, Trust Insights can guide you every step of the way.

Here’s how you can get started:

Schedule a Consultation: Let’s discuss your organization’s unique challenges and how we can help. Click here to book a meeting.
Download the 5P Framework Guide: Learn how to apply this powerful tool to your governance strategy. Download the guide here.

Are you being haunted by digital ghosts? Reach out and tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss your digital ghost. You will learn whether employers can put your digital ghost to work, the legal and ethical implications of employers using your digital assets, how to safeguard your digital likeness, and what you need to negotiate with your employer.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we did a Halloween special on AI-powered share of voice. Catch the episode replay here!

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👉 New: Generative AI for Hospitality

In this week’s Data Diaries, let’s take a sneak peek at some data from our upcoming series, the 12 Days of AI Use Cases. This is the successor to the previous series, 12 Days of Data. We’re retiring that series for a couple of reasons.

First, more than half of the data we featured in the series, such as Instagram and Facebook data, is simply no longer available. Meta discontinued access to that data this past July and made it clear there were no viable alternatives except for a few select organizations.

Second, as we’ve seen this past year with generative AI hogging the spotlight, data is incredibly valuable but as an ingredient for other uses. Data by itself doesn’t do much unless you take action with it.

So to that end, we’re launching the 12 Days of AI Use Cases beginning tomorrow, December 5, on the blog.

However, to fuel that, we needed to know what the major AI use cases are. We looked at all the digital ink spilled this year about AI use cases on every publication tracked by AHREFS with a domain rating of 25 or higher and used Meta’s Llama 3.1 model to read and classify them all in one of the 7 generative AI use case categories:

Generation : AI makes content
Summarization : AI summarizes and condenses content
Extraction : AI extracts subsets of content from larger content
Rewriting : AI transforms content from one format to another
Classification : AI organizes content
Question answering : AI answers questions from content
Synthesis : AI aggregates content

How are people being told to use generative AI? What’s been written in 2024? Out of 13,295 use cases from 1,949 articles, we found:

34.2% of use cases were about generation
28% of use cases were about classification
14% of use cases were about summarization
9.4% of use cases were about question answering
6.4% of use cases were about synthesis
4.5% of use cases were about rewriting
3.5% of use cases were about extraction

Keep in mind that we looked broadly at all generative AI use cases, not just marketing ones. This is from every publication in every industry that the AHREFS catalog knows about.

The irony here is that generation, the top use case, is the skill that generative AI has the most trouble doing. Generation often requires extensive prompting, examples, and steering to do a good job, whereas tasks like summarization need very little guidance, yet rank #3 on the chart of things that people have written about generative AI in 2024.

What’s the key takeaway? It’s important to know and understand the media diet when it comes to a technology like generative AI. Just because a use case category is popular doesn’t mean it’s the best fit for the technology.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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