History indicates that my AI-preneurship would HELP me succeed as a third-party candidate
Re: “HELP me succeed”
Details below.
The relevant history
From 2007 book The Populist Vision, published by Oxford University Press:
“[T]he Populist revolt [in the U.S. during the 1890s] reflected a conflict over divergent paths of modern capitalist development.
. . . By the 1880s, two firmly entrenched parties dominated the political scene. At the national level, Democrats and Republicans held much in common as they shared a conservatism that was acceptable to the financial and corporate establishment.
. . . Progressive Era legislation in the first years of the new [i.e., 20th] century expanded the role of government in American life and laid the foundations of modern political development. Populism provided an impetus for this modernizing process, with many of their demands co-opted and refashioned by progressive Democrats and Republicans.”
“The Farmers’ Alliance [was] the largest and most important constituency of what would become the Populist coalition [of the 1890s].
. . . From its earliest stirring [in the 1870s], the Farmers’ Alliance defined itself as an educational movement.
. . . The farmers needed to organize for self-education to better engage the complex problems of modern society . . . To get people reading and thinking required what [Alliance president Macune] described as a modern educational machine. The engine driving this machine was the reform press.
. . . By the late 1880s, the Alliance had grown to an intellectual enterprise that stretched across much of rural America . . . [The Alliance] built lecture circuits across thirty states and a network of approximately one thousand weekly newspapers.”
“The Farmers’ Alliance . . . realized that without the political levers of control, even the best-laid business plans would come to naught. . . . Convictions about . . . political action flowed directly from business strategies.
. . . Most of the Populist ‘revolt’ took place not in the streets but in lodge meetings and convention halls, where participants pored over problems of commerce and government and adopted resolutions for the creation or expansion of state and federal agencies, institutes, commissions, departments and bureaus.”
“A Texas experiment provided the most widely imitated prototype . . . The Texas Farmers’ Alliance Exchange . . . would offer Texas cotton growers all the advantages of a centralized and regulated market, with a rational structure and direct access to credit and to the commercial centers . . . From Georgia to California the Farmers’ Alliance set up state exchanges.”
From 2016 book This Is an Uprising: How Nonviolent Revolt Is Shaping the Twenty-First Century:
After two years of research, Chenoweth crunched the numbers. Examining the first data set of 323 campaigns [i.e., social movements], she . . . found a direct correlation between the success of a campaign and the popular involvement [in it.]
. . . Chenoweth found that, in fact, “no campaigns failed once they’d achieved the active and sustained participation of just 3.5 percent of the population[”] . . .
This is not an insignificant number: in the United States, 3.5 percent of the population would mean gaining the support of some 11 million individuals.
. . . Spurring people to this level of engagement is not easy.
Re: my AI-preneurship
From ike1952yang2020ruscica2024.substack.com/p/threat-to-many-or-most-people (hereafter referred to as URL):
— Summary (some details follow; more below) —
Key goal: owning/operating (OOing) the leading online-market for AI and customized-education (i.e., OOing the Amazon of AICE (AoAICE)).
A key to OOing AoAICE is OOing the most popular implementation of my Amazon-/VC-praised* design that:
will yield a next-gen variant of LinkedIn (NGLI)
fixes the fatal flaw of 2003 “sensation” BlogShares.com
A key to OOing NGLI is providing said disruptive innovations.
* From said 2004 email sent to me by Amazon’s first Director of Personalization:
We thought a lot about reputation systems. We thought a bit about personalized advertising systems. We thought a lot about blogging and social networking systems. . . . [W]e’ve been working a very similar vein to the one you describe . . .
— Name of my planned startup —
The Opportunity Services Group (OSG)
— Re: NGLI —
OSG’s 1.0 implementation of the site/app will feature:
a market for the advertisement spaces on solo-blogger blogs (e.g., portfolio blogs)*
a virtual currency (cash transactions will be supported also)
Prices in OSG’s virtual currency (OVC) will contain/reflect only truthful peer ratings of work samples. Ratings of this kind are a top predictor of work performance, according to a much-cited meta-analysis of 85 years of personnel-selection research (6149 citations as of December 9, 2021)**. Other top predictors of work performance are often unavailable (e.g., test results). So OVC prices will be ideal for ranking people within individual job/skill categories. These rankings will make it much easier for Jane Q. Upwardly-Mobile to identify others who (can) best complement her (ditto for John Q.).
* An ad space sold for OVC will typically be on the homepage (i.e., front page) of the seller’s blog; key reasons: 1) sales of spaces for OVC will occur via weekly auctions, 2) per week, each blogger will be able to sell only one ad space for OVC (which space is sold can vary weekly). Keywords re: said auctions: sealed-bid, second-price; combinatorial auctions via fractional allocations, so each week’s auction will provide a “spot” market and an “up-front” market; traders will make these markets “information-efficient.”
** From 2015 book Work Rules!: Insights from Inside Google That Will Transform How You Live and Lead, by Google’s then head of “People Operations”:
. . .
From the Schmidt-Hunter paper linked-to above:
— Name of OSG’s planned site/app —
Adver-ties
— Re: Adver-ties will be a debugged version of BlogShares.com —
From a 2003 article* on rediff.com:
The latest sensation that’s grabbing the attention of netizens is BlogShares . . . an online stock market in which you get to speculate on the future of your favourite blogs. . . . Every player gets 500 BlogShare dollars upon signup.
. . . How you play BlogShares depends on what you want from it. For some, the objective is to get their blogs on the Top 100 Index.
. . . At the end of a three-week phase of beta testing, there were a staggering 40,000 listed blogs. Over 5000 active players carry out thousands of transactions every day . . .
* See the References section.
— Re: the fatal flaw of BlogShares —
The price mechanism was easily gamed. From the rediff.com article:
[Inbound] links are the assets that drive valuations.
— Re: bloggers will be able to parlay a high and/or fast-rising ad rate in OVC into cash via: 1) sales of other ad spaces, 2) affiliate-marketing commissions, 3) subscriptions —
KWs: influencer marketing (IM), antidote to the epidemic of IM fraud. Some details follow; more are (linked-to) below.
Izea: 71% of influencers had a blog in 2018; 39% of advertisers sponsored blog posts in 2018; 67% of social-media users in 2020 aspired to be paid social-media influencers.
Mediakix: 44% of advertisers considered blogs to be among the social-media channels that were most important for IM in 2020 (Facebook: 45%; Twitter: 33%; LinkedIn: 19%); 50% of advertisers considered fraud the #1 drawback of IM in 2020.
— Re: a high and/or fast-rising ad rate in OVC will be achievable partly via OSG’s prediction markets (OPMs) —
High prices/rankings in OPMs will serve as PageRank-like pointers to high-quality blogs. Details are linked-to below. Keywords: OPM prices denominated in OVC.
From 2018 book Prediction Machines: The Simple Economics of Artificial Intelligence, published by Harvard Business School Press:
AI is a prediction technology . . .
. . . What will new AI technologies make so cheap? Prediction.
. . . When prediction is cheap, there will be more prediction and more complements to prediction.
— More precedents for Adver-ties —
Google’s PageRank search algorithm (first use of hyperlinks to inform search results)
peer assessments associated with popular MOOCs (massively open online courses)
LinkExchange.com
GitHub.com
PageRank 1.0 was based on insights from social-network analysis that were decades old when PageRank was conceived. (Similarly, LinkedIn et al. could’ve productized said 85-years-of-personnel-selection-research long ago.)
From a 1998 paper co-authored by Google’s founders:
There has been a great deal of work on academic-citation analysis [Gar[19]95]. Goffman [Gof71] . . .
Number of commercial search-engines launched before Google: 20.
From 2013 paper “Tuned Models of Peer Assessment in MOOCs,” co-authored by several employees of MOOC provider Coursera ($447M raised):
Peer assessment—which has been historically used for logistical, pedagogical, metacognitive, and affective benefits . . .—offers a promising solution that can scale the grading of complex assignments in courses with tens or even hundreds of thousands of students.
From the 1998 article in The Wall Street Journal titled “Microsoft Buys LinkExchange For About $250 Million in Stock”:
LinkExchange . . . places ad banners on about 400,000 Web sites, though many of those sites are obscure personal homepages [e.g., blogs] . . .
LinkExchange, founded in 1996, has taken a unique approach that has allowed it to grow its network of sites very quickly. The company allows member Web sites to advertise for free on other sites throughout the LinkExchange network—provided they agree to return the favor.
From a 2016 article on the website of Harvard Business Review (my emphases):
How can companies get a better idea of which skills employees and job candidates have? . . . One potential model is GitHub.
. . . Ideally, this [desired variant of GitHub] would also be a social network and e-portfolio, allowing an employer to see samples of work and trust that the skills presented had been validated by others. (The social component of GitHub is important to underscore because other developers validate and consume another developer’s work. This contrasts starkly with the “skills”— if we can call them that—that users can tag so quickly on LinkedIn, such as “higher education” or even “ninja.”)
— More re: the business case for Adver-ties —
LinkedIn was acquired by Microsoft for $26.2 billion in 2016.
Title of a 2018 article on TechRepublic.com:
Why Linkedin + GitHub profiles could be the hidden gem in $7.5B Microsoft acquisition [of GitHub]
— Re: popularizing Adver-ties will be foundational for popularizing OSG’s market for AI & CE —
Outputs from activity at and around Adver-ties (e.g., prices) will be inputs to OPMs. After Adver-ties catalyzes the popularization of 1.0 OPMs, outputs from activity at and around the OPMs (e.g., 2.0 OPMs) will be inputs to Adver-ties (i.e., the popularization of Adver-ties and OPMs will become mutually reinforcing). Both sets of said outputs will be inputs to OSG’s market for AI/CE (e.g., the outputs will help/enable consumers of AI/CE to feel confident that they’re receiving value for their expenditures).
Precedent for said dependencies between markets
financial-capital markets (e.g., prices output by an equities market are inputs to an equity-derivatives market)
Re: outputs from Adver-ties being inputs to OSG’s AI/CE market
From the 2015 article in The New York Times titled “Finding a Career Track in LinkedIn Profiles”:
[M]uch of what we need to know about the changing labor market is crowdsourced in real time. And many of those digital breadcrumbs end up in LinkedIn profiles.
From a 2015 interview of Michael Horn, co-author of 2008 book Disrupting Class: How Disruptive Innovation Will Change the Way the World Learns:
[W]e’re really in the early beginnings of the dramatic revolution that we’ve seen in a lot of other technology sectors where really smart recommendation engines come in and assist the student in picking and choosing their unique path. . . .
In order to really go towards adaptive learning, you need huge numbers of students on your platform . . .
We need platforms that can collect the data we need and can make better use of data so that we can figure out different ways to serve different learners.
Disrupting Class was co-authored by the late Harvard Business School professor Clayton Christensen, originator of the canonical models of disruptive innovation.
From 2016 book Thank You for Being Late: An Optimist’s Guide to Thriving in the Age of Accelerations:
At the high end of the labor ladder, professionals already have a global intelligent algorithm to draw on: LinkedIn, the career professional social networking site. But its founders now want to extend that intelligent algorithm to the whole world of work by creating a global “economic graph.” Here is how LinkedIn’s CEO, Jeff Weiner, describes it on his company blog:
Reid Hoffman and the other founders of LinkedIn initially created a platform to help people tap the value of their professional networks, and developed an infrastructure that could map those relationships up to three degrees. In doing so, they provided the foundation for what would eventually become the world’s largest professional graph.
Our current long-term vision at LinkedIn is to extend this professional graph into an economic graph by digitally manifesting every economic opportunity [i.e., job] in the world (full-time and temporary); the skills required to obtain those opportunities; the profiles for every company in the world offering those opportunities; the professional profiles for every one of the roughly 3.3 billion people in the global workforce; and subsequently overlay the professional knowledge of those individuals and companies onto the “graph” [so that individual professionals could share their expertise and experience with anyone].
Anyone will be able to access intelligent networks such as LinkedIn’s global graph, see what skills are in demand or available, and even offer up online courses. You might teach knitting or editing or gardening or plumbing or engine repair. So many more people will be incentivized to offer their expertise to others, and the market for it will be vastly expanded.
Added Weiner:
With the existence of an economic graph, we could look at where the jobs are in any given locality, identify the fastest growing jobs in that area, the skills required to obtain those jobs, the skills of the existing aggregate workforce there, and then quantify the size of the gap. Even more importantly, we could then provide a feed of that data to local vocational training facilities, junior colleges, etc., so they could develop a just-in-time curriculum that provides local job seekers the skills they need to obtain the jobs that are and will be, and not just the jobs that once were.
Separately, we could provide current college students the ability to see the career paths of all of their school’s alumni by company, geography, and functional role.
From 2018 book A New U: Faster + Cheaper Alternatives to College, by a VC whose focus is education:
“LinkedIn CEO Jeff Weiner’s vision for an ‘economic graph’ is the clearest expression by any technology company of the competency-marketplace future.”
“[T]echnological developments will complete the faster + cheaper revolution. The resulting ‘competency marketplaces’ . . .”
“The historic disconnect between higher education and employer needs is a data problem. . . .
Technology has begun to change this . . . first via the increasing availability of competency data: e-portfolios . . .”
— End of excerpt from URL —
See URL for more about my AI-preneurship.
Re: presentation-errors above
From 2012 book APE: Author, Publisher, Entrepreneur—How to Publish a Book, co-authored by Guy Kawasaki, a former chief evangelist at Apple:
Every time I turn in the “final” copy of a book [Kawasaki has (co-)authored twelve books], I believe that it’s perfect. In APE’s case, upward of seventy-five people reviewed the manuscript, and [co-author] Shawn [Welch] and I read it until we were sick of it. Take a wild guess at how many errors our copy editor found. The answer is 1,500. [APE is 410 pages.]
And, of course, I’m preoccupied with preventing/subduing said threat to many/most people . . .