INBOX INSIGHTS: Professional Communities, Red Teaming Custom GPTs

INBOX INSIGHTS: Professional Communities, Red Teaming Custom GPTs (1/10) :: View in browser

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Over winter break, I spent a lot of time reflecting and taking in information. Part of that was taking classes with the Peloton Community. If you don’t belong to the Peloton Community, you might see it as a “cult”. If you do belong, you know why you keep going back for more.

Part of what I get out of this community are things to think about. All the instructors have catchphrases. Many of them use their classes to share stories, drop wisdom, and provoke thought. Some of the quotes that have stuck with me are:

It’s not either/or, it’s both/and
Make modifications not excuses
Progress over perfection
Acknowledge the fear and do it anyway

I cannot say that in all the years I’ve been working out I’ve ever gotten so much out of a program. And a lot of it comes down to how strong the community is. I recently joined a team with Gini Dietrich (if you know how she rides, you know that I need your prayers). A few years ago, this isn’t something I would have ever done. I’ve always been someone who thought I was better off doing it alone.

Until now.

The Peloton community got me thinking. Why is it so accepted to join a community in your personal life and seek out support? And why isn’t true in the professional world? We build teams but then we silo them. We ask people to perform at their best, but we don’t provide them a support system.

In fitness, you’re encouraged to find a coach and an accountability partner (Gini is mine). The more people you have involved, the more successful you’ll be. This is true both of team and individual sports. In the workplace, you’re told to get your work done, stop distracting other people, and figure it out on your own.

Big, huge disclaimer – this is not true of all workplaces. There are many companies that have embraced community culture. For those that haven’t, I’m talking to you. I’ve mostly worked at companies that want you to be a self-sufficient lone wolf. Everything else is a waste of time. When I look back at those experiences, I realize how much I missed out on.

My goal today is to help you convince your company why prioritizing communities is a smart move in 2024.

Support, encouragement and accountability

Since the dawn of time, humans have been in search of their tribe. Modern day communities are no different. We inherently want to find our “people”. Groups with shared interests can support and encourage us. They can also offer accountability where we otherwise might not find it at our companies or on our teams.

Continual learning and diverse perspectives

One of the key advantages of joining a community is gaining access to individuals from diverse backgrounds. I grew up in a town where the majority of people shared similar characteristics and experiences as me. It wasn’t until I went to college that I became aware of how limited my understanding of the world had been. Engaging with a diverse community allows you to pose questions that yield a wide range of perspectives. As members share their personal stories, you’ll discover yourself learning from their unique experiences.

A few companies ago, I didn’t realize how sheltered I was in the professional world. My ecosystem consisted of my coworkers, their experiences, and well…that was it. I spent a decade learning everything I knew about business from the same small group of people. When I left that company for a new role, my mind was blown. I felt like I knew nothing and I was so far behind everyone else. I wish I been a part of a professional community outside of my job. I wish I had known that communities existed. If I had, I would have been set up for more success when I moved on. I may have even been able to bring more back to my current role and not felt the need to leave.

Expanding your network

Joining a professional community has an obvious benefit. It allows you to expand your network. You have an opportunity to meet and connect with people outside of your normal circles. If you keep your circle small, you’ll limit your opportunities and your learning will be narrow. Being a better professional, even a better person, means opening up your world and your mind.

Let’s make 2024 the year of normalizing being a part of something bigger, asking for support, and learning from our peers. The motto of Peloton is “together we go far”. What is your motto going to be?

Did you know that our Generative AI for Marketers course has its own dedicated community? You not only have access to our Analytics for Marketers community, but you also have a group dedicated just to you and the other students. This group gives you access to other who are learning about generative AI. You’ll also have access to the instructors to help answer your questions.

Is your company prioritizing communities as part of the culture? Reply to this email to tell me or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this week’s In-Ear Insights, Katie and Chris talk through some of the considerations that Custom GPT makers and consumers should keep in mind as OpenAI’s Custom GPT Store opens for business this week. Learn what pitfalls to avoid!

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

Last time on So What? The Marketing Analytics and Insights Livestream, we did an AMA on generative AI. Catch the episode replay here!

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Red Teaming Custom GPTs, Part 1 of 3

In this week’s podcast, Katie and I talked about red teaming an LLM, which is a QA testing method to see if you can coerce a language model into doing something it’s not supposed to do. So for those folks who are thinking about deploying something like a Custom GPT, let’s look at the very basics of red teaming – and by basics, I mean the absolute basics. This is the equivalent of fitness advice that starts with “buy appropriate shoes and try running from your front door to the corner”. This is not comprehensive or complete, because red teaming – cybersecurity – is an entire profession and industry.

Red teaming follows the same structure as pretty much everything else – the Trust Insights 5P Framework: purpose, people, process, platform, performance. The difference in red teaming is that you’re looking for opposition to the 5Ps.

Your first step, if you haven’t done it already, is to determine what the 5Ps are for your language model application. Today we’ll use Custom GPTs as the example, but this applies broadly to any language model implementation.

Purpose: What is your Custom GPT supposed to do? People: Who are the intended users? Process: How is the user expected to interact with the Custom GPT? Platform: What features of the OpenAI platform does the Custom GPT need access to? Performance: Does the Custom GPT fulfill the designated purpose?

Once you document your 5Ps for your Custom GPT, invert the questions. This is how you start to build out a red teaming plan of action. We’ll start with purpose this week.

Inversion of Purpose

Purpose: What is your Custom GPT not supposed to do?

In red teaming for language models, there are generally two major categories of risks we need to account for, two forms of anti-purpose that are so critical that we need to spell them out for ourselves and our stakeholders.

Undesirable outcomes that are unhelpful, harmful, or untruthful
Access to data, systems, or functions that shouldn’t be permitted

One of your first tasks when building a Custom GPT (or any AI, really) is to dig into these two categories and spell them out.

What would be unhelpful behavior from your Custom GPT? Unhelpful is a question of alignment – when a user asks the Custom GPT to perform a task or produce an output, and it fails to do so in a way that meets the user’s expectations, that’s unhelpful. Given the purpose of your Custom GPT, what specific things would be unhelpful? For example, if you made a Custom GPT to give tax advice, and the Custom GPT refused to give tax advice when asked, that would be unhelpful. Make a list of unhelpful behaviors that a Custom GPT should not perform.

What is harmful behavior in the context of your Custom GPT? Certainly, behaving in a biased way is an obvious one, expressing points of view that are biased, racist, sexist, bigoted, or derogatory. But those behaviors aren’t always so overt; sometimes, derogatory behavior can masquerade as civil communication, but really isn’t. For example, if your Custom GPT asks the user’s name and then produces different quality outputs based on inferences about the user’s gender or ethnicity, that’s harmful. Make a list of the harmful behaviors that a Custom GPT should not perform.

What constitutes unacceptably untruthful from your Custom GPT? Bad advice? Wrong information? Could customers perceive – correctly or not – that advice given from a Custom GPT that you’ve branded as yours means you endorse its outputs, and that false information is approved by you? For example, if a user asked a Custom GPT to tell them about one of your products, and it gave information about a competitor’s product instead, that would be untruthful. Make a list of untruthful behaviors that a Custom GPT should not perform.

Next time, we’ll tackle inversion of people, process, and platform. Stay tuned!

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