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Will reliability of information in SaaS products become the new subscription tiers:
Standard AI model [Good]
Enhanced AI model [Better]
Human-verified [Best]
ā
If I asked you, āWhen someone turns in a work assignment, how accurate is it? 80%, 90%, 95% or perhaps 100%?ā
We donāt think this way about coworkersā spreadsheets. But we will probably think this way about AI & this will very likely change the way product managers on-board users.
When was the last time you signed up for a SaaS & wondered : Would the data be accurate? Would the database corrupt my data? Would the report be correct?
But today, with every AI software now tucking a disclaimer at the bottom of the page, we will be wondering. āGemini may display inaccurate info, including about people, so double-check its responsesā & āChatGPT/Claude can make mistakes. Check important infoā are two examples.
In the early days of this epoch, mistakes will be common. Over time, less so, as accuracies improve.
The more important the work, the greater peoplesā need to be confident the AI is correct. We will demand much better than human error rates. Self-driving cars provide an extreme example of this trust fall.Ā WaymoĀ & Cruise have published data arguing self-driving cars areĀ 65-94% safer.
Yet, 2/3 of Americans surveyed by the AAAĀ fear them.
We suffer from a cognitive bias : work performed by a human is likely more trustworthy because we understand the biases & the limitations. AIs are aĀ Schrodingerās catĀ stuffed in a black box. We donāt comprehend how the box works (yet), nor can we believe our eyes if the feline is dead or alive when we see it.
New product on-boarding will need to mitigate this bias.
One path may be starting with low-value tasks where the software-maker has tested exhaustively the potential inputs & outputs. Another tactic may be to provide a human-in-the-loop to check the AIās work. Citations, references, & other forms of fact-checking will be a core part of the product experience. Independent testing might be another path.
As with any new colleague, the first impressions & a series of small wins will determine the personās trust. Severe errors in the future will erode confidence, that must be rebuilt - likely with the help of human support teams who will explain, develop tests for the future, & assure users.
I recently asked a financial LLM to analyze NVIDIAās annual report. A question about the companyāsĀ increase in dividend amountĀ vaporized its credibility, raising the question : is it less work to do the analysis myself than to check the AIās work?
That will be the trust fall for AI. Will the software catch us if we trust it?
Stunning new views of Mars being sent back by @MarsCuriosity from the slopes of Mt Sharp in Gale Crater... just look at the different shapes, colours and textures of those rocks... Images credit: NASA/JPL-Caltech/MSSS/fredk/S Atkinson
This is the resource guide I wish I'd had when I started exploring #climate solutions.
If youāre looking for #climatetech newsletters, job boards, communities, explainers, solution libraries, & more, you'll find them here.
Letās go! šŖ
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Loved talking all things product marketing, climate tech, and leadership with @DEVorourke on the Embracing Erosion podcast.
šš”š
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Professor @emollick has some of the most practical content on the applicationsāand implicationsāof AI in business. For anyone who isnāt clear yet how disruptive this technology is going to be in the very near term, check out Mollickās latest post.
āTo see why these tools can be so disruptive, I want to revisit my old experiment of giving myself 30 minutes to launch a product. I last did this 10 months ago ā forever in AI time ā so it seemed unfair to give myself a half hour again. Letās try doing the work in under a minute.ā
āFive reasonably high-quality drafts were done in under a minute. I had renderings of a few trendy kitchens, a three-page syllabus (that wasnāt half bad), a thirteen-page slide deck with speaker notes, an almost 1,000-word market research summary, and a product launch strategy (with draft emails) for one of Wharton Interactiveās teaching games that was really solid. A few more interactions with the AI, and a bit more time, and they might have been excellent.ā
āTo paraphrase Kratzenbergās First Law: āAI at work is neither good nor bad; nor is it neutral.ā AI does not automatically improve the experience of work, nor does it automatically rob us of meaning or replace workers. How leaders and employees use the technology will determine whether it is good or bad. But AI also isnāt neutral. The use of AI will inevitably lead to deep and profound changes.ā
If you havenāt already subscribed to his One Useful Thing Substack, do it today.
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NEW paper:
Deep emissions cuts the priority.
Carbon removal is a longer term solution.
But we need to get moving on CDR now š§µ
Ā
The next 10 years is the crucial āFormative Phaseā
for novel carbon dioxide removal (nCDR).Ā
https://t.co/OPKxJcyL7j
Excited to share that @IndigoAg just expanded our Scope 3 product suite, making it easier for companies with agriculture in their supply chain to measure & reduce Scope 3 emissions.
Get started today & scale as youāre ready.
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We've got a new song coming out inĀ January. Sign up for our email list for a first listen of Helmet, the new single fromĀ our 10th album, Jump Rope (coming in 2024).
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Thereās nothing like a @buffalotomband show.
But the next best thing is a personal shoutout from Chris Colbourn. š
Thanks Chris!! Canāt wait to see you guys again live!
People who live on the West side of each time zone go to bed later (dark blue), get less sleep, make less money, and suffer more diseases on average, as a map from this study shows!
https://t.co/J6zL1QDK5l