Persuasion ≠ manipulation
Teaching, recommendation, advocacy, art and advertising all persuade. Deception, hidden sponsorship, fake scarcity, fabricated social proof, obstructed cancellation and exploitative targeting cross different ethical lines.
Attention is finite
No person can read, watch, verify, answer, learn, care about, or respond to everything available. Information abundance therefore creates a filtering problem.
The question is not whether information is filtered. It always is. The question is who controls the filter, according to what objective, and whether the person can understand or change it.
Diagnosis
Engagement ≠ value
Clicks, watch time, comments and return frequency measure behavior. They do not directly measure truth, learning, wisdom, relationship quality or long-term satisfaction.
“Screen time” is too crude
Video calling family, editing music, reading research, gaming with friends, doomscrolling and navigating transit are not one standardized exposure.
Children deserve stronger protection
Development, uncertainty, persuasive systems and sensitive data justify greater caution than “let the market optimize engagement and see what happens.”
News is information and environment
People need public information, but continuous exposure can become a threat stream far beyond one person’s capacity to act.
Algorithms are editors with different governance
Ranking systems choose what becomes visible. Users should have meaningful context and alternatives where practical.
Advertising can fund useful things
The important questions are what data persuasion requires, what behavior the business model rewards, whether sponsorship is visible, and whether refusal is real.
Political persuasion needs higher standards
Argument and campaigning are legitimate. Fabricated grassroots support, impersonation, hidden sponsorship, doxxing, harassment and covert vulnerability targeting are not.
AI lowers media-production cost
That expands creation and accessibility while also making spam, impersonation, synthetic reviews, propaganda and mass persuasion cheaper.
Speech ≠ amplification
Legal speech rights, platform rules, editorial selection, recommendation, paid amplification and personal filtering are different categories.
Media literacy cannot carry everything
People should learn source checking and statistics, but deceptive systems cannot be excused simply by demanding infinitely skeptical users.
Field Guide
Choose some information directly. Bookmarks, RSS, newsletters, library sources, saved searches, primary documents and chronological/subscribed modes can reduce complete dependence on recommendation feeds.
Separate “need to know” from “can keep watching.” Ask what decision the next refresh will actually change.
Remove some nonessential interruptions. Keep useful services while reducing notifications, badges and promotional alerts; measure what becomes worse as well as better.
Protect sleep from an information environment that never sleeps. Do-not-disturb, device placement and work-notification boundaries are environmental design, not moral purity.
Build direct relationships with people and publications you value. Do not require an algorithm to repeatedly rediscover choices you already made.
Slow down high-stakes sharing. Health, elections, war, emergencies, accusations and financial claims deserve stronger sourcing before redistribution.
Program
Clear advertising identity
Paid persuasion should be recognizable. Sponsorship should not masquerade as ordinary social proof.
Restrict deceptive design
False countdowns, hidden recurring charges, disguised ads, obstructed cancellation and materially misleading consent flows belong inside consumer-protection policy.
Meaningful feed controls
Recommendation should not be the only doorway. Chronological/subscribed, search, reduced-personalization or reset options can preserve direct choice where practical.
Stronger defaults for children
Test age-appropriate privacy, reduced profiling, notification limits, recommendation transparency and research access while measuring privacy and speech tradeoffs.
Direct publishing & open knowledge
Websites, RSS, email, libraries, archives, open standards and interoperable protocols preserve routes around a few dominant feeds.
Provenance in an AI media world
Content credentials, source chains, authenticated institutional communication and verifiable originals can strengthen trust signals in high-stakes contexts.
Plural journalism funding
Advertising, subscriptions, membership, philanthropy, public media, nonprofit ownership and events all create incentives; compare them openly.
Political ads preserve civic agency
Identify the source, avoid fabricated support and covert vulnerability targeting, correct material errors, and make refusal/unsubscribe real.
Measure more than engagement
Task completion, learning, trust calibration, time saved, successful exit, informed satisfaction and downstream harm can matter alongside clicks.
Evidence notes
Deceptive design
The U.S. Federal Trade Commission has documented “dark pattern” designs that can trick or manipulate consumers into purchases, subscriptions, privacy choices or data sharing. FTC ↗
Youth social media
The U.S. Surgeon General’s advisory concluded current evidence is insufficient to conclude social media is adequately safe for children and adolescents and called for stronger research, safeguards, family tools and platform responsibility. HHS ↗
AI risk and oversight
NIST’s AI Risk Management Framework treats risk as socio-technical and emphasizes governance, measurement, human-AI configuration, monitoring and accountability rather than treating “human in the loop” as a magic phrase. NIST ↗
Human Scale’s own advertising standard
Human Scale has to obey the rule it proposes for everyone else.
Identify Thomas / Human Scale as the source.
No fake accounts or fabricated grassroots support.
No repeated unwanted outreach after silence.
No fear-based targeting using sensitive vulnerabilities.
No deceptive scarcity or countdowns.
Correct material factual errors.
Link evidence when making empirical claims.
Distinguish “we believe” from “research shows.”
Promote useful tools, results, maps, receipts or experiments—not only demands for attention.
Make leaving easy.
Every advertisement should leave the audience with something useful even if they never become a Human Scale supporter.
A Human Scale test for attention & media
What is the user trying to do?
What is the system trying to optimize?
Is paid persuasion clearly identified?
Are material choices reversible?
Can the person reach chosen information without an algorithmic feed?
What data is used to personalize persuasion?
Are sensitive vulnerabilities being exploited?
Is refusal easy enough to be meaningful?
Does the system create unnecessary interruption?
Are children given stronger protections?
Can important claims be traced to sources?
Does AI generation weaken provenance or accountability?
Is there a route to correction or appeal?
Are speech, ranking, recommendation and paid amplification being distinguished?
What would count as value besides engagement?
What evidence would make us change the design?
The direction
The future will contain more media, AI, simulation, personalization and information than any individual can absorb. The answer is not to demand infinite human attention.
A humane information system does not win by capturing the most attention. It wins by helping people use their attention for lives they actually value.