For those of you who are avid readers. Firstly, Thank you. By now, I am certain that you understand my approach and style to more robust topics; Circuitous, layered, and paralleled in approach. If you'll allow me, the present topic at bar is likewise complex and multi-layered as well as multi-faceted; I will present some structural pieces then tie them together once the pieces are properly laid. BE WARNED, it may yet take some time to get there. But, I do believe the analysis is worthwhile.

And, if you missed the previous Blog, please visit here:

Meta-Analysis: AI's Impact on the U.S. Economy (2020 – 2026) and beyond [Small businesses. WHAT NOW?]

This being 3-part: please take your time to walk through the material, or binge-read. Player's Choice🙌

Part I: YOU are the product

Many were born into "day-zero" communities or neighborhoods. There was no farm, factory, or history prior to your family moving or setting in a place. Not: 6th generation lumber mill town. Not: 4th generation farmer on the same land. Not: 3rd generation factory worker (in a factory town) that was build alongside your family at the beginning.

Again, mere context, this is not a disparagement. Due to updated financial regulations and liberalization of capital, government dollars, and social/legal programs, the 1960s, and 1970s saw a dramatic rise in people going to university (newly supported and funded government loans), as well as 1980s and 1990s rise in government support for broader and multi-factored home lending. More wealth, more opportunity, more jobs, more homes, and more capitalism became more available to more people.

As this upward trend of capital, market activity, investment, and mobility became possible, the multi-generational towns and industries were on the decline; reasons included globalization, expansion of multi-lateral and multi-chain supplychains, cost-shoring, higher and greater market cap with larger public corporations continuously driving more shareholder "value" and corporate returns, climate & particulate goals/targets, and increasingly faster technologies for transmission, communication, and data. Jobs were in larger urban centers. Products were more widely available in larger urban centers. As more people flocked to urban centers, the buildout boom stemming from the 1940s (post-WWII) continued.

During this era, the PRODUCT was the product; the height of industrialization, materials sciences, manufacturing, and globalization. And yes, all of the tropes as well as statistics supported this dynamic; single-income families, inflation and purchasing power (multiples of median income aligned with real estate pricing). Yes that was all true. Once this product, supplychain, delivery, and cheap goods model was cemented by the 2010s, another quieter yet pervasive trend was building in the background.

One would think that the great recession of 2008-2015 would yield additional caution with respect to fast financing, over-leveraging purchase power, and a general cooling of consumerism: but industry and human psychology had other ideas. The causes and perhaps motivations behind this inconspicuous lack of due decorum or caution is beyond the scope of this current publication. However, broadly, there are a few bright-line contributors that are worth a mention.

Smart Phone ubiquity (slab/glass) phone design and the software/infrastructure surrounding its adoption started in this era, 2010s and on. Recall the sold out iPhone feeding frenzies of every November (just in time for the Holidays). Layer on top, fast-shipping and guaranteed delivery (Amazon and other retailers) coupled with the liberalization of supplychain entrypoints: DROP-SHIPPING (where the origin of sale did not have to be the origin of production).

Globalization was in full swing: almost every country could buy "American" or "European" or "Japanese" products that were shipped directly from white-box factories in Asia or Southeast Asia. Major retailers also onboarded independent stores and 3rd-party sellers who could supply products to a seemingly ever-growing and endless audience.

All the ingredients were in place for the infinite scroll-product-click & buy glitch:

• real estate crash post 2008 - learned from that, not doing that again. Renting is the key

• Liberalized trade routes and supplychain redundancy

• Expedited Shipping and arrival

• Customs & Import authorities seemed to follow suit - relaxing tariffs, checkpoints, and random audits

• Technical products & infrastructure caught up: internet on your phone

• Applications - were better than their web experience counterparts

Real Time | Product | Service | Supplychain | Delivery | and technical infrastructure seemed to be, for the first time, commensurate with and a digital analog to REAL LIFE. Mind you, this was the front-facing business: PRODUCTS, GOODS, and abundance of "STUFF."

Behind the scenes, making it all work was : frameworks, web applications, inventory software, data tables, arrays, middleware, huge back-end engineering, architecture/scaling, cloud services, data centers. The entire back-office economy created to support the "STUFF" revolution. These services, not to be left out; because come on, as large as the product companies and platforms were, an equal if not greater amount of capital was also required to build out the technical and digital infrastructure to support all this "STUFF."

The software and technical infrastructure companies also had boardrooms, investors, stock prices, quarterly reports, growth targets, and BUNDL/HODL/STAKR price fixers and shortsellers to market make and swing trade. OK OK, a bit hyperbolic, most companies do not serve at the pleasure of market speculators, but merely lay hostage to their market activities. Still, the market dynamics of upward surge or downward swings affect almost any company of size and scale regardless of sector, product, or domain. Money is Money. And when there is money to be made, market action is what investors and speculators seek.

How do we get to the "YOU ARE THE PRODUCT" portion of this discussion you might ask? While your thesis may differ from this author's perspective; the confluence of customer data, public sentiment, scale for augmentation and testing, as well as personal identifiable information (shipping address, credit cart information, buying subscriptions, stocking up on office supplies, refill for coffee, etc. . . ) are all necessary datapoints in service of the PRODUCTS and "STUFF" delivery industry.

Follow the bouncing ball: the "STUFF" economy was built to support execution and delivery of the "STUFF." Yet, on the other side of that wide counter sitting in the backoffice was seemingly non-contiguous but voluminous customer data. Alone, untethered, and unused.

Whatever to do with this personally identifying, detailed sentiment and buying habits data of hundreds of millions of worldwide consumers?

Eventually, having exploited all angles of consumer "STUFFs" delivery model, product selection infinity, and having made every color, texture, size, and variation of products, there wasn't much growth remaining. The infrastructure was built. The customer service handled. The supplychain, modularized and segmented (for redundancy). New sellers can get verified and show off their product and follow the usual paths of promotion, social attribution, media releases, interviews, and micro-creator sublimation. From an enterprise perspective, maintenance and servicing means that the job was done and someone was about to be out of a job because INNOVATION = NEW

New to market. New to me. New to the segment. Repackaged ideas with new applications. As long as it is NEW, the market may respond positively and cater growth toward PE ratios, PPS, GDP, dividend value, NEW capital, NEW buildouts, NEW industries, NEW sectors, NEW NEW NEW.

So while looking to the back office and utilizing customer data for other purposes may not have been the next logical step, it is in the value-chain of rational outcomes when reviewing the whole picture of the fast-retail, fast-shipping, unlimited products, everything on subscription- "STUFFs" economy.

Eventually, YOU, ME, we were all on the menu for feasting. Our data. Our preferences. Our purchasing habits. Our patterns. Our "digital person" or personhood lay squarely in the crosshairs of big enterprise.

How was that meal? OH. Sooooo good. Even so, the undertow of heavier and more insidious attempts of data mining and data gathering was not received with open arms. Consumers and the public at large began to understand the iconoclast world of big data monitoring, increasingly opaque terms of service, and endless subscriptions.

Overview of Sentiment Shifts on "You Are the Product"

The phrase "you are the product" encapsulates the long-standing critique of tech business models where user data is harvested, commodified, and sold (primarily for advertising) in exchange for "free" services. Over the last 5-10 years (roughly 2015–2025), public sentiment has undergone a notable shift: from a mix of acceptance and mild concern in the mid-2010s to widespread anxiety, cynicism, and demands for greater control by the early 2020s. This evolution is driven by high-profile data breaches (e.g., Cambridge Analytica in 2018), the rise of regulations like GDPR (2018), and growing awareness of surveillance capitalism.

Key drivers include:

• Increased Awareness: Scandals amplified perceptions of exploitation, leading to a "trust deficit" in Big Tech.

• Regulatory and Cultural Pushback: Laws and movements (e.g., #DeleteFacebook) empowered users, fostering demands for ownership and compensation.

• Generational Divide: Younger users (Gen Z, millennials) show higher privacy prioritization, while overall acceptance has declined.

Data from surveys, reports, and social media reflects this trajectory. Below, I summarize trends chronologically, drawing on consumer surveys and online discourse.

Key Data and Trends (2015–2025)

Early Period (2015–2018): Growing but Mixed Awareness

• In 2015, UK consumer attitudes toward data collection showed relative tolerance. A Direct Marketing Association (DMA) survey found 31% of respondents were "unwilling to exchange personal information," but this dropped to 24% by later waves, with "unconcerned" users rising from 16% to 22%. This suggested a migration toward acceptance, with many viewing data sharing as a fair trade for convenience. Awareness of regulations like the EU's Data Protection Regulation was high, fostering a sense of empowerment rather than alarm. Source

• US data echoed this: A 2015 KPMG poll ranked Google highly in trust for data handling (ahead of Amazon and Microsoft), with 69% of consumers expressing confidence in Big Tech's stewardship. Social media sentiment was nascent but critical; for instance, a 2019 WIRED post highlighted emerging calls for users to be paid for their data, signaling early pushback against the "product" model. Source

Mid-Period (2019–2022): Surge in Concern Post-Scandals

• By 2019–2020, trust eroded significantly. Pew Research (November 2019 update) showed a subtle shift: consumers increasingly favored government intervention over self-regulation by tech firms for data protection, with only 29% finding it "easy to understand" how companies protect data. A 2020 KPMG study (May poll) reinforced this, noting heightened anxiety amid COVID-19 data tracking, with 50% of consumers uncomfortable sharing personal data yet 66% expecting personalized ads—highlighting the "have your cake and eat it too" tension. Source

• Online discourse intensified. X (formerly Twitter) posts from this era, like Jack Dorsey's 2019 thread on proprietary algorithms directing attention (rather than just hosting content), and Andrew Yang's 2020 op-ed decrying users as "sold" behavioral products, captured rising frustration. A 2020 post by Per Axbom emphasized behavioral manipulation over simplistic "product" framing, underscoring autonomy loss. Source

• The Conference Board's 2021–2022 US survey revealed "widespread anxiety and cynicism" about data practices, higher than global peers, with consumers viewing data use as exploitative. Source

Recent Period (2023–2025): Demand for Ownership and Regulation

• Privacy has become a "competitive differentiator." Secureframe's 2024 compilation of stats (from Pew, Cisco, etc.) showed only 29% of consumers trust companies' data protection explanations, with data privacy integral to brand loyalty. Deloitte's 2025 Connected Consumer Survey (3,524 US respondents) found rising expectations for transparency and security, with "data responsibility" key to trust and spending—pairing it with innovation could boost loyalty. Source

• X sentiment in 2023–2025 reflects exhaustion with surveillance. Posts like Session's 2023 thread called surveillance capitalism's end imminent, while 2024–2025 threads decried data as "exploitation" and demanded ownership (e.g., "Your identity is not a product for sale"). A 2025 post noted AI transparency and data privacy as top brand concerns on social media. Broader frustration with "constant panoptic surveillance" appeared in 2024–2025, linking it to diminished agency. Source

• Egon Zehnder's 2025 trends report highlighted tech's response: on-device AI and encryption to limit data exposure, driven by regulatory pressures and trust erosion. McKinsey's 2025 State of the Consumer noted localized shopping preferences partly as privacy backlash against global data giants. Source

This shift signals a tipping point: users are rejecting the "free-for-data" bargain, favoring paid models or decentralized alternatives where they control (and potentially monetize) their data. Tech firms ignoring this risk backlash, while those prioritizing privacy (e.g., via end-to-end encryption) gain loyalty. Signal, WhatsApp, and Torrents. The piracy / data awareness trends have interesting interplay and correlation with the broader marketplace. Please comment and let me know whether you'd like a separate discussion on these historical trends.

Continue to

PART II: HERE