Almost Timely News: Resistance to AI (2023-05-14) :: View in Browser
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What’s On My Mind: Resistance to AI
Over the past week, I’ve had a chance to talk about AI – generative AI in particular – in several different industries, like healthcare, consulting, education, entertainment, and marketing. In all these different cases, there’s been a common, unsurprising thread: a significant amount of resistance by a portion of the audience. Not to me, not to the material, but to the very concept of generative AI itself.
Here are a few anonymized discussion points:
- AI isn’t as good as what humans can create
- AI will make us all lazy and incompetent
- AI is going to cause mass layoffs
Let’s dig into a few of these points and present what we can for a balanced perspective on them.
AI isn’t as good as what humans can create
The blanket statement that AI isn’t as good as what humans create comes from a place of fear, fear that machines will in fact take many of the good paying creative jobs. As with all these statements, there’s nuance to it. Let’s say that quality of work is a normal distribution, a bell curve. Where does AI fall on that bell curve?
Based on stuff like what ChatGPT comes up with – especially with good, complex prompts – I think it’s fair to say that large language models create good content. Not great, not amazing, not Pulitzer Prize winning, but good. The tools are better than mediocre, which is where they were a year ago, and they’re certainly better than the word salad they spit out three years ago.
So the question for creators is, where are you individually on the bell curve? Are you a good creator? Then AI is your peer in terms of content quality. Are you a great creator? Then AI is your lesser. Are you a mediocre creator? Then AI is your better.
Here’s the question we have to ask, as human creators: does the work we do merit great, amazing, or Pulitzer Prize-winning capabilities? For some things, like our next book, I’d argue yes, we need great quality. For a press release? Good quality is probably, well, good enough.
The true challenge we human creators have to face isn’t AI today. It’s how fast AI is progressing. Three years ago, generative AI was pretty bad. Half the time, it was like watching chimpanzees play Scrabble. But there were glimmers, particularly on highly-templated content, that generative AI had promise.
Today, large language models create good content. They knock out press releases. They create competent, informative blog posts. They write moderately compelling emails. That’s how fast they’ve evolved in three years. How fast have your skills grown in that same time? That’s the challenge we face. Those of you who are great content creators, what will it take for you to become amazing? Those of you who are amazing, what will it take for you to create content at top-tier award winning levels?
AI will make us lazy and incompetent
The second claim that AI will make us lazy and incompetent has some truth to it as well. How many people under the age of 30 feel confident in their ability to navigate to an unknown destination using only a paper map? Fewer than those who feel confident in doing so with a map application on their smartphones. How many people feel confident looking up a topic in a hardcover encyclopedia? Fewer than those who feel confident Googling for something.
There’s absolutely no question that technology has changed how we think, how we work, how we get things done. We have, without reasonable doubt, lost some skills along the way. We’ve replaced map reading with map application navigation. We’ve replaced memorizing friends’ phone numbers with contact files on our smartphones. But in doing so, we’ve freed up good chunks of our cognitive capacity to do other things.
People – and all life, really – will always default to doing things as easily as possible, with as little effort as possible. That’s nature. Natural selection favors those who can conserve resources over those who expend them fruitlessly. Anything we can do to make things better, faster, or cheaper, we do. The role of AI in that scenario should be obvious: we will use it to do less, to defer more to machines.
This is not new. This is a tale as old as time. We invented stone tools so we could stop using our hands to dig in the dirt. We created machines to do heavy labor so we wouldn’t have to. In the same way that machines alleviated much of our strain in the Industrial Revolution, AI will do the same in the Intelligence Revolution. And just as those revolutions allowed us to benefit more broadly in the past, so will that also happen in the present.
This particular argument is behind some of what I think are the dumbest moves you can make. In school after school, office after office, I see people sticking their heads in the sand. They’re pretending AI doesn’t exist – from the Writer’s Guild of America to the local high school. I got an email the other day from our local school announcing the ban of ChatGPT and reassuring parents it had been blocked on the school’s Internet. Never mind standalone services like GPT4ALL that can run locally on your computer without Internet access at all, clearly the folks who have implemented these rules don’t understand how smartphones work.
Prohibiting some people from using AI and permitting others to use it only creates more fractures and divisions in society. If we want an equitable, fair society, we need to make sure everyone has equal access to powerful tools and equal access for how to use them well. If we want a just and moral society, we need to ensure people learn morals and justice alongside the tools, not forbidding the use of the tools and then wondering why human nature leads people to misuse the tools they stumbled upon with no guidance at all.
AI will cause mass layoffs
Will it all be smooth going? Of course not. More and more labor economists, partnering with AI thought leaders, are estimating that AI will consume 30% or so of current jobs. I think that’s on the low side, personally. I feel like the figure is probably closer to 50%. But just as the vast majority of the workforce labored in fields three hundred years ago and very, very few people comparatively do so now, so will we expect to see similar shifts in knowledge work. What those new jobs will be, we don’t know.
This statement I think is the most true of the three. AI will cause substantial changes in labor, in how we do work. And those changes will have substantial economic impacts, impacts that we are underestimating right now. Whether it’s 5%, 30%, 50%, the percentages don’t matter as much as the recognition that change is happening right now in a giant way, and the sooner we recognize it, the sooner we can do something about it.
Some of those solutions may be things like universal basic income, funded by “robot taxes”. The implementation of that is still murky, but it’s clear that any profession which uses language or creativity – and let’s face it, that’s a lot of professions – will be significantly impacted by AI, especially in capitalist economies where AI leads to dramatic increases in profitability when used effectively, at the expense of wages and workers.
Other solutions will be all about the integration and supervision of AI by humans. This is critically important and harkens back to point 2: people do tend to take the path of least resistance. Having humans continue to be fact checkers, supervisors, conductors of the machine orchestra if you will, will be our most important roles because machines are only as good as the data they’re trained on. And let’s face it, a lot of what’s on the Internet is crap. Any implementation of AI which promises to be turnkey, fire and forget is likely dangerous. You wouldn’t just send your self driving car out for a Sunday drive without you in it, right? Nor should you just deploy AI and then forget about it.
Are the reasons for opposition of AI that we started with valid? Yes and no. There are real concerns underlying those reasons. There are real viewpoints that need to be acknowledged and addressed, and real nuances that we need to communicate. There are also plenty of bad actors who will misuse AI in every way possible, and we need to be prepared for that as well. The only way to accomplish all this is with human integration at every opportunity and a willingness to intentionally sacrifice some efficiency, some effectiveness, some profitability, to ensure a balanced use of AI that’s more beneficial than harmful.
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ICYMI: In Case You Missed it
Besides the newly-refreshed Google Analytics 4 course I’m relentlessly promoting (sorry not sorry), I recommend the piece on how to regulate generative AI. Spoiler: you can’t. Watch the piece to learn what we should be doing instead.
- You Ask, I Answer: How to Regulate Generative AI?
- You Ask, I Answer: Company Claims of AI Generated Content?
- You Ask, I Answer: Large Language Model Capability Limits?
- You Ask, I Answer: Sales Roles Impacted by ChatGPT?
- You Ask, I Answer: Detection of AI Content?
- Almost Timely News, May 7, 2023: The Next Wave of Generative AI
- We’re Augmenting Your Intelligence
- So What? Social Scheduling Tools Bake-off
Skill Up With Classes
These are just a few of the classes I have available over at the Trust Insights website that you can take.
- ⭐️ The Marketing Singularity: How Generative AI Means the End of Marketing As We Knew It
- Powering Up Your LinkedIn Profile (For Job Hunters) 2023 Edition
- Measurement Strategies for Agencies
- Empower Your Marketing With Private Social Media Communities
- Exploratory Data Analysis: The Missing Ingredient for AI
- How AI is Changing Marketing, 2022 Edition
- How to Prove Social Media ROI
- Proving Social Media ROI
- Paradise by the Analytics Dashboard Light: How to Create Impactful Dashboards and Reports
Get Back to Work
Folks who post jobs in the free Analytics for Marketers Slack community may have those jobs shared here, too. If you’re looking for work, check out these recent open positions, and check out the Slack group for the comprehensive list.
- Ai/Ml Audio Research Engineer at Antares Audio Strategies
- Cloud Data Engineer at Kindred Group
- Data Engineer at Ikazia ziekenhuis
- Data Engineering Lead at Lesmills
- Engineering Intern (Large Language Models) at Moonhub
- Machine Learning Consultant at SportsIcon
- Senior Data Engineer at Chicago Public Media
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What makes this course different? Here’s the thing about LinkedIn. Unlike other social networks, LinkedIn’s engineers regularly publish very technical papers about exactly how LinkedIn works. I read the papers, put all the clues together about the different algorithms that make LinkedIn work, and then create advice based on those technical clues. So I’m a lot more confident in suggestions about what works on LinkedIn because of that firsthand information than other social networks.
If you find it valuable, please share it with anyone who might need help tuning up their LinkedIn efforts for things like job hunting.
What I’m Reading: Your Stuff
Let’s look at the most interesting content from around the web on topics you care about, some of which you might have even written.
Social Media Marketing
- Meta Begins Testing Generative AI Elements for Facebook and Instagram Ads via Social Media Today
- TikToks Testing a New Process to Help Musicians Maximize Exposure in App via Social Media Today
- What You Need to Know About Social Media Copyright via Sprout Social
Media and Content
- Content Is No Longer King. Why Studios Have the Upper Hand in WGA Strike Negotiations via MediaVillage
- ChatGPT buzz pushes the metaverse into the marketing-strategy backseat: Planned investments are shifted to AI via Agility PR Solutions
- What Is Content Intelligence?
SEO, Google, and Paid Media
- How To Use Your Website Data To See If Your Buyers Journey Really Works
- Examining the impact of Google’s Helpful Content Update
- ChatGPT: The Future of Content Creation For SEO via ReadWrite
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What makes this different than other training courses?
- You’ll learn how Google Tag Manager and Google Data Studio form the essential companion pieces to Google Analytics 4, and how to use them all together
- You’ll learn how marketers specifically should use Google Analytics 4, including the new Explore Hub with real world applications and use cases
- You’ll learn how to determine if a migration was done correctly, and especially what things are likely to go wrong
- You’ll even learn how to hire (or be hired) for Google Analytics 4 talent specifically, not just general Google Analytics
- And finally, you’ll learn how to rearrange Google Analytics 4’s menus to be a lot more sensible because that bothers everyone
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Tools, Machine Learning, and AI
- Best AI Checkers (Free): Is This Essay Written By AI? via Dataconomy
- Ray Kurzweil Rebuts Calls To Pause AI Research
- Explained: What Is PaLM 2 (vs GPT4) via Dataconomy
Analytics, Stats, and Data Science
- Interview Questions on NoSQL via Analytics Vidhya
- Dropbox Lays off 500 Employees as an Effect of AI
- Top Data Science Ph.D. Dissertations (2019-2020) via insideBIGDATA
All Things IBM
- Bring light to the black box via IBM Blog
- IBM Watson Orchestrate: Unlocking new levels of productivity for every employee via IBM Blog
Dealer’s Choice : Random Stuff
- AI presents political peril for 2024 with threat to mislead voters
- Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum | Health Informatics | JAMA Internal Medicine | JAMA Network
- AI Learns to Walk (deep reinforcement learning) – YouTube
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How to Stay in Touch
Let’s make sure we’re connected in the places it suits you best. Here’s where you can find different content:
- My blog – daily videos, blog posts, and podcast episodes
- My YouTube channel – daily videos, conference talks, and all things video
- My company, Trust Insights – marketing analytics help
- My podcast, Marketing over Coffee – weekly episodes of what’s worth noting in marketing
- My second podcast, In-Ear Insights – the Trust Insights weekly podcast focused on data and analytics
- On Twitter – multiple daily updates of marketing news
- On LinkedIn – daily videos and news
- On Instagram – personal photos and travels
- My free Slack discussion forum, Analytics for Marketers – open conversations about marketing and analytics
Events I’ll Be At
Here’s where I’m speaking and attending. Say hi if you’re at an event also:
- B2B Ignite, Chicago, May 2023
- MAICON, Cleveland, July 2023
- ISBM, Chicago, September 2023
- Content Marketing World, DC, September 2023
- MarketingProfs B2B Forum, Boston, October 2023
Events marked with a physical location may become virtual if conditions and safety warrant it.
If you’re an event organizer, let me help your event shine. Visit my speaking page for more details.
Can’t be at an event? Stop by my private Slack group instead, Analytics for Marketers.
Events with links have purchased sponsorships in this newsletter and as a result, I receive direct financial compensation for promoting them.
Advertisements in this newsletter have paid to be promoted, and as a result, I receive direct financial compensation for promoting them.
My company, Trust Insights, maintains business partnerships with companies including, but not limited to, IBM, Cisco Systems, Amazon, Talkwalker, MarketingProfs, MarketMuse, Agorapulse, Hubspot, Informa, Demandbase, The Marketing AI Institute, and others. While links shared from partners are not explicit endorsements, nor do they directly financially benefit Trust Insights, a commercial relationship exists for which Trust Insights may receive indirect financial benefit, and thus I may receive indirect financial benefit from them as well.
Thanks for subscribing and reading this far. I appreciate it. As always, thank you for your support, your attention, and your kindness.
See you next week,
Christopher S. Penn
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- Best Practices for Public Speaking Pages
- How to Measure the Marketing Impact of Public Speaking
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- How To Start Your Public Speaking Career
- What Is The Difference Between Analysis and Insight?
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