E4: Politicizing the pandemic, Police reform, Biden's ideal VP, Twitter vs. Facebook on free speech & more with David Sacks & David Friedberg

Summary of the prediction
Chamath (June 20, 2020) predicted that from that point forward:

1. “There is not a single country government that can tolerate future lockdowns” and populations would revolt rather than accept further broad lockdowns or shelter‑in‑place orders.
2. Therefore, instead of renewed broad lockdowns, we would see a “start and stop” world of localized closures (e.g., some Apple stores closing temporarily) “for the foreseeable future.”
3. “It’s just not possible to ask people now to go back into any form of quarantine or shelter in place. I just don’t think they’ll do it.”

Key interpretation points

• Timeframe: “for the foreseeable future” starting June 2020 – in practical terms, we assess against what happened in late 2020 and 2021, when further COVID waves hit.
• Claim is universal: “not a single country government” can do future lockdowns / quarantine / shelter in place with compliance.
• He’s contrasting nationwide / broad lockdowns vs. only localized, start‑stop measures.

What actually happened

1. Europe re‑imposed mass/national lockdowns in late 2020 with substantial compliance

   • The UK announced a second national lockdown for England from 5 November to 2 December 2020, closing non‑essential retail, hospitality (except takeaway), and restricting people to staying at home except for limited reasons.
   • France imposed a second nationwide lockdown starting 30 October 2020, requiring people to stay at home except for essential reasons and closing non‑essential businesses.
   • Germany introduced a nationwide “lockdown light” in November 2020, followed by stricter nationwide measures (including closure of most retail, schools in many states, and stay‑at‑home provisions) in December 2020.
     These were clearly government‑ordered, national‑scale lockdowns, not just scattered local closures.

2. Asia also had renewed strict, sometimes national, stay‑home orders

   • India, after lifting its first nationwide lockdown in mid‑2020, implemented various state‑wide and city‑wide lockdowns later in 2020 and 2021 (e.g., in Maharashtra during the 2021 Delta wave), with stay‑at‑home orders and broad business closures backed by police enforcement.
   • Multiple Asia‑Pacific countries (e.g., Malaysia, the Philippines) re‑imposed nationwide or near‑nationwide movement control orders with stay‑home rules and closure of most non‑essential sectors during later waves.
     These were again broad, government‑imposed lockdowns, not just localized, company‑level “start and stop” adjustments.

3. Compliance remained significant, even if imperfect

   • In these second and third waves, governments did face more public frustration, protests and “pandemic fatigue,” but large segments of the population did in fact comply with staying home, school closures, and business shutdowns, as evidenced by mobility data and mainstream reporting (e.g., reduced public transport use and retail footfall during the second UK and French lockdowns).
   • There were protests in various countries, but they did not prevent governments from imposing or sustaining these renewed lockdowns for weeks to months.

4. The world did not remain purely in a localized ‘start–stop’ corporate‑driven mode

   • While there were localized measures (city‑level closures, office outbreaks, Apple/retail store re‑closures), those co‑existed with broad, renewed lockdowns at regional or national level in many countries through late 2020 and into 2021.
   • In other words, the actual pattern was: governments did re‑impose sweeping lockdowns and shelter‑in‑place rules; it was not limited to the firm‑level “Apple closes some stores for a few weeks” dynamic he described.

Why the prediction is judged wrong

Chamath’s prediction contained two strong components:

1. "Not a single country government" can do future lockdowns / shelter in place
   This is directly falsified by the UK, France, Germany, and many others re‑imposing national or large‑scale stay‑at‑home orders and business closures from late 2020 onward, with large‑scale (if imperfect) public compliance.

2. We’ll instead be stuck only in localized ‘start and stop’ closures
   That dynamic did happen at the margin (local and corporate closures), but it did not replace broad government lockdowns; both occurred. The prediction, as phrased, rules out broad lockdowns, which did in fact occur multiple times.

Because

• the claim was universal (“not a single country government”), and
• multiple clear counterexamples occurred within months, and
• enough time has passed to evaluate “for the foreseeable future,”

the prediction is best classified as wrong.

Evidence since June 2020 matches Chamath Palihapitiya’s claim that many concrete police-reform measures (use-of-force rules, training, misconduct/decertification frameworks, and even some union‑contract changes) would actually be enacted in at least some U.S. jurisdictions, often with support across party lines.

• Within roughly a year of George Floyd’s murder, at least 30 states plus Washington, D.C., enacted one or more statewide policing reforms; 25 of those states and D.C. changed law on use of force, duties to intervene/report/render aid, or misconduct reporting and decertification, including bans or tight limits on chokeholds and new reporting/databasing requirements. (brennancenter.org)
• The National Conference of State Legislatures found that from May 25–Dec 31, 2020, 36 states and D.C. introduced over 700 police‑accountability bills, with nearly 100 enacted, showing broad legislative follow‑through rather than rhetoric alone. (ncsl.org)
• States such as Virginia passed sweeping packages in a 2020 special session: banning most chokeholds and no‑knock warrants, requiring officers to intervene in excessive force, limiting minor‑infraction stops, creating statewide codes of conduct and standardized training, expanding decertification of officers, authorizing AG pattern‑or‑practice investigations, and establishing the MARCUS mental‑health crisis response system. (en.wikipedia.org) These are precisely the kinds of training, use‑of‑force, and oversight reforms discussed in 2020 debates.
• Numerous cities and states adopted additional policy changes: Louisville’s Breonna’s Law unanimously banned no‑knock warrants; other jurisdictions revised chokehold rules, duty‑to‑intervene policies, and data‑collection practices; and Minneapolis entered a court‑enforceable consent decree to overhaul police training and use‑of‑force policies after a DOJ investigation. (en.wikipedia.org)
• Some reforms explicitly involved union or contract structures: Boston’s 2023–25 contract with the Boston Police Patrolmen’s Association, whose prior contract expired in June 2020, is described by the city as its first to include operational reforms, including a defined list of serious offenses that are no longer eligible for arbitration (limiting a key union protection), changes to paid‑detail and overtime systems, and reduced on‑duty union release. (boston.gov)
• Palihapitiya also argued that different ideologies would often converge on similar reforms for their own reasons. Post‑2020 legislation supports this at least at the state level: for example, Arizona’s HB 2650, requiring independent investigation of critical force incidents by an outside agency, passed with bipartisan support, and Republican‑led Arkansas created a statewide task force to review police training, certification, and standards in response to the protests. (en.wikipedia.org)
• By contrast, comprehensive federal reforms such as the George Floyd Justice in Policing Act repeatedly stalled in the U.S. Senate, indicating that national bipartisan consensus was limited. (en.wikipedia.org) But Chamath’s normalized prediction only required that many of the discussed reforms be implemented somewhere in the U.S., not that Congress would enact a sweeping federal package.

Taken together, the record shows that a substantial number of concrete police‑reform measures on use of force, training, oversight/decertification, data reporting, and even some union‑contract provisions were in fact enacted in multiple jurisdictions across the country after June 2020, often with at least some bipartisan support. That aligns with the substance of his prediction, so it is best judged as right overall.

Chamath’s prediction that the largest U.S. tech firms would face much stronger government headwinds—more regulation, higher taxation, and constraints on their operations, with breakup risk at the extreme—has broadly played out since 2020, even though no company has actually been broken up.

Antitrust and regulatory pressure dramatically increased. Since 2020, the U.S. Department of Justice and state AGs have brought multiple landmark antitrust cases against Google (search and ad-tech), winning liability rulings that Google illegally monopolized both search and key ad-tech markets, with structural remedies (including potential divestitures) on the table. (en.wikipedia.org) The FTC’s ongoing case against Meta over Instagram and WhatsApp could force divestitures, and is now at trial, explicitly raising the prospect of unwinding those acquisitions. (en.wikipedia.org) The DOJ and several states sued Apple in 2024, alleging it illegally monopolizes smartphone markets and stating that structural breakup remedies are possible, again signaling serious breakup risk even if no breakup has yet occurred. (cnbc.com) The FTC has also filed a major monopolization suit against Amazon and separately extracted a record $2.5 billion settlement (including a $1 billion civil penalty) over Prime “dark patterns,” illustrating an aggressive enforcement stance. (ftc.gov) In parallel, the Biden administration issued Executive Order 14036 to launch a “whole-of-government” competition policy, and its antitrust leaders (Lina Khan at the FTC, Jonathan Kanter at DOJ) are widely described as having “reinvigorated” antitrust enforcement, bringing high-profile cases against Google, Apple, Amazon, Meta, Microsoft and others at a pace not seen in decades. (en.wikipedia.org)

Regulation and compliance burdens on Big Tech increased sharply. At the U.S. state level, a growing patchwork of comprehensive privacy laws (California’s CCPA/CPRA plus Virginia, Colorado, Connecticut, Utah, Texas, Oregon and others) now impose stricter data-collection, consent, and consumer-rights rules on large data-driven companies like Google, Meta, Apple, Amazon and Microsoft, raising compliance costs and constraining data use compared to the pre‑2020 environment. (jdsupra.com) Internationally, the EU’s Digital Markets Act formally designated Alphabet, Amazon, Apple, Meta and Microsoft as “gatekeepers” subject to far-reaching obligations on self‑preferencing, app stores, interoperability, and data use; the Commission has already opened non‑compliance investigations into Alphabet, Apple and Meta that could force major product and business‑model changes. (euronews.com) These measures have not stopped these companies from growing, but they clearly represent the sort of regulatory headwinds and operational constraints Chamath described.

Taxation and financial penalties have also become more punitive. The Inflation Reduction Act of 2022 introduced a 15% corporate minimum tax on large corporations with over $1 billion in profits, directly targeting the roughly 200 largest companies—including the biggest tech firms—that had often paid effective rates below 15%; this is explicitly framed as closing loopholes and raising their tax burden relative to the prior regime. (forbes.com) In addition, Big Tech firms have faced escalating fines and monetary remedies: for example, the EU levied a multibillion‑dollar antitrust fine on Google’s ad‑tech business with the possibility of structural remedies if Google does not adequately change its conduct, and the FTC’s $2.5 billion Amazon settlement is its largest civil penalty ever. (apnews.com) These developments fall squarely within Chamath’s “regulated, overtaxed and slowed down at a minimum” scenario. While the extreme outcome of actual breakups has not (yet) occurred, the substantial increase in antitrust litigation, regulation, compliance burden, and effective tax pressure on the largest U.S. tech companies means the core directional claim of his prediction has been borne out.

Overall, the prediction that users would sort themselves into ideologically distinct platforms and choose services that reinforce their existing political views has largely played out, even though the specific forecast about Twitter staying left-leaning turned out backward.

Key evidence:

1. Clear partisan splits in which platforms people use (self‑segregation)
   A 2025 Pew study finds distinct party gaps by platform: Democrats are more likely than Republicans to use TikTok, Reddit, Bluesky, Threads and WhatsApp, while Republicans are more likely to use X (Twitter) and Truth Social. (pewresearch.org) This is exactly the kind of sorting-by-politics across platforms Chamath described.

2. Explicitly partisan platforms have emerged and become strongly skewed
   The same 2025 Pew data, summarized by The Verge, shows Truth Social is heavily Republican (6% of Republicans use it vs 1% of Democrats) while Bluesky is heavily Democratic (8% of Democrats vs 1% of Republicans). (theverge.com) These are concrete examples of people choosing platforms that “feed them what they want to hear.”

3. Twitter/X shifted from a Democratic-leaning to a Republican-leaning user base
   In early 2021, U.S. Twitter users were noticeably more likely to be Democrats than Republicans (about 32% vs 17%). (pewresearch.org) After Elon Musk’s takeover, multiple studies show a sharp realignment: Republicans now report using X at slightly higher rates than Democrats, and Republican users have grown significantly more positive about X’s impact on democracy while Democrats have become more negative. (theverge.com) That contradicts Chamath’s directional call that Twitter would stay a left‑leaning, coastal enclave, but it strongly supports his broader mechanism: users moved toward the platform whose political climate matched their views.

4. Facebook as ‘middle America’ with politically mixed but older-leaning news consumers
   Pew reports that Facebook news consumers are older than those on TikTok, Instagram, or X, and are almost evenly split politically (47% Republican/leaning vs 46% Democrat/leaning). (pewresearch.org) Perceptions of political content on Facebook lean slightly liberal overall, though Republicans in particular see it as mostly liberal. (pewresearch.org) This supports the “broad, middle‑America, older” user base idea more than a clean right‑only skew, but it is still consistent with his claim that different audiences gather on different platforms.

5. Political content and experiences differ sharply by platform and party
   A 2024 Pew report shows X is uniquely saturated with politics (74% of users see at least some political content, vs 52% on Facebook and less on Instagram/TikTok), and Republicans and Democrats report very different experiences and perceptions of bias on each service. (pewresearch.org) This indicates that platforms are serving distinct political information environments that align with user ideology.

Synthesis:

• Chamath’s high-level prediction — ongoing ideological self‑segregation by platform, with people gravitating toward services that validate their views — is strongly supported by the rise of explicitly partisan networks (Truth Social, Bluesky) and by clear party-based splits in platform use and experience.
• His specific mapping (Facebook = more right/middle America; Twitter = affluent, coastal left) is only partly accurate. Facebook is indeed older and broadly “middle America,” but not clearly majority‑right; and Twitter/X actually flipped from left‑leaning to more right‑leaning post‑Musk.

Because the central, forward-looking claim about self‑segregation and echo‑chamber platform choice came true in a strong way, despite some incorrect details about which side dominates which platform, the best overall judgment is “right” rather than “wrong” or “ambiguous.”

Summary
Friedberg predicted in June 2020 that “there’s going to be a staged release of vaccines [for COVID‑19] that’ll probably … start in Q4 of this year.” Q4 2020 runs from October 1 to December 31, 2020.

What actually happened

• On December 11, 2020, the U.S. Food and Drug Administration (FDA) issued the first Emergency Use Authorization (EUA) for a COVID‑19 vaccine, the Pfizer‑BioNTech (BNT162b2) mRNA vaccine, for use in individuals 16 years of age and older. This is an official authorization allowing distribution and use of the vaccine in the U.S. in December 2020 (Q4 2020).
• Shortly after, in December 2020, initial doses were shipped and administered in the U.S., marking the beginning of a staged rollout, starting with high‑priority groups (healthcare workers, nursing‑home residents) and expanding to broader populations in 2021.

Assessment versus prediction

• Timing: He predicted initial/staged release would start in Q4 2020 rather than only later in 2021. The first authorization and rollout did indeed begin in December 2020, which is within Q4 2020.
• Staged release: The rollout was explicitly phased by priority group and supply availability, matching his description of a “staged release.”

Because both the quarter (Q4 2020) and the staged nature of the rollout match what occurred, this prediction is right.

Evidence shows this prediction was right.

Key facts:

• Pfizer and BioNTech submitted their EUA request to the U.S. FDA on November 20, 2020 for their COVID‑19 vaccine, BNT162b2.
• The FDA granted Emergency Use Authorization (EUA) on December 11, 2020 for individuals 16 years and older.
• The CDC’s Advisory Committee on Immunization Practices (ACIP) recommended that healthcare personnel and residents of long‑term care facilities be in the initial Phase 1a priority group for vaccination.
• Vaccine shipments began within days of the EUA, and frontline healthcare workers started receiving doses in mid‑December 2020, which is clearly within Q4 2020 (October–December).

Representative sources:

• The FDA’s announcement of the EUA for the Pfizer‑BioNTech COVID‑19 vaccine on December 11, 2020, including the indication and timing of authorization.
• CDC/ACIP guidance naming healthcare personnel and long‑term care facility residents as the first priority group, and contemporaneous news reports showing initial vaccinations of healthcare workers beginning in mid‑December 2020 in the U.S.

Because doses were in fact available and distributed to healthcare and other frontline workers in December 2020, which is within Q4 2020, Friedberg’s prediction that “we could have doses that are available for distribution to healthcare workers and frontline people in Q4 of this year” was borne out by events.

Evidence strongly supports both parts of Friedberg’s prediction: (1) that COVID‑19 vaccination in the U.S. would become highly politicized, and (2) that a substantial share of Americans would refuse or fail to get vaccinated, with persistent non‑uptake similar in spirit to measles.

1. Politicization of the COVID‑19 vaccine

Multiple surveys and analyses show that political identity became one of the strongest predictors of COVID‑19 vaccine attitudes and behavior:

• A 2021 Pew Research Center analysis found large partisan gaps in vaccination: by August 2021, 86% of Democrats (and Democratic leaners) reported at least one dose vs. only about 60% of Republicans and Republican leaners, reflecting clear politicization of uptake. (pewresearch.org)
• A Gallup review identifies partisanship as “one of the most significant correlates of vaccine hesitancy,” with 46% of Republicans saying they would not get the vaccine, vs. just 6% of Democrats. (news.gallup.com)
• A 2023 Pew study shows Democrats were roughly twice as likely as Republicans to say the benefits of COVID‑19 vaccines outweigh the risks (84% vs. 40%), and that one‑third of Republicans said they did not get a COVID‑19 vaccine, compared with 9% of Democrats. (pewresearch.org)
• By 2024–2025, Pew and other reporting explicitly describe vaccines—especially updated COVID shots and even routine childhood vaccines—as sharply polarized by party, with large Republican majorities saying they will skip updated COVID shots and support for mandates dropping sharply among Republicans. (pewresearch.org)

This pattern shows that vaccination behavior and attitudes became deeply intertwined with partisan identity, matching Friedberg’s forecast that the vaccine would be heavily politicized.

2. A significant portion of Americans refused or failed to get vaccinated

Friedberg’s normalized prediction says that because of this politicization, the U.S. would not achieve near‑universal uptake; instead, a meaningful minority would remain unvaccinated, akin to persistent non‑vaccination seen with measles.

COVID‑19 primary series / any dose:

• CDC data show that by late 2022, after broad availability and extensive campaigns, about 80.5% of the total U.S. population had received at least one COVID‑19 dose and about 68.8% had completed a primary series. That means roughly 19–31% of the population remained either completely unvaccinated or not fully vaccinated, even after ample time and supply. (archive.cdc.gov)
• National Health Interview Survey data for 2022 show 79.7% of U.S. adults had received at least one dose, implying around 20% of adults had never gotten any COVID‑19 vaccine. (cdc.gov)
• A 2023 Pew survey found 13% of U.S. adults saying they had not received a COVID‑19 vaccine at all, with much higher non‑vaccination among younger adults (24% of 18–29‑year‑olds). (pewresearch.org) These are non‑trivial, persistent pockets of refusal or non‑uptake.

Updated/booster doses:

• As the pandemic progressed, refusal to stay current became even more pronounced. In 2024, Pew found only 28% of U.S. adults reported getting the then‑updated COVID vaccine, meaning over 70% had not. (pewresearch.org)
• For the 2024–25 season, Pew reported that about 60% of Americans said they probably would not get an updated COVID‑19 vaccine, with 81% of Republicans saying they planned to skip it—again showing large, durable gaps in uptake. (pewresearch.org)

Analogy to measles non‑vaccination:

Friedberg compared COVID to measles, where a small but persistent unvaccinated minority creates ongoing vulnerability.

• CDC‑linked reporting shows that U.S. MMR (measles, mumps, rubella) coverage among kindergarteners has fallen from about 95.2% in 2019–2020 to around 92.5–92.7% in recent school years, below the ~95% herd‑immunity target and associated with rising measles outbreaks; exemptions and unvaccinated clusters drive these outbreaks. (reuters.com)

While exact percentages differ (COVID coverage never approached childhood MMR’s previous 95%+ levels, and booster coverage is much lower), the pattern Friedberg described—ongoing substantial non‑vaccination, enough to sustain disease risk—clearly materialized for COVID as well. A sizeable minority, strongly concentrated along political lines, has consistently refused or failed to get initial shots and especially boosters.

Conclusion

By late 2022 and through 2024–2025, COVID‑19 vaccination in the U.S. was heavily politicized, and a meaningful share of Americans either never got vaccinated or stopped staying up to date, mirroring the kind of persistent non‑vaccination problem seen with measles (though at different absolute levels). Given the data on partisan polarization and enduring non‑uptake, Friedberg’s prediction is best categorized as right.

Assessment window
Sacks was speaking on June 20, 2020, and explicitly said the picture could be very different in “five [to] six months,” i.e., roughly November–December 2020—right around the 2020 election.

What actually happened by November–December 2020

1. Election outcome
   By November 3, 2020, Donald Trump’s political position did not become more favorable; he lost reelection. Joe Biden won 306 electoral votes to Trump’s 232 and won the national popular vote 51.3% to 46.8% (a 4.5‑point margin). (en.wikipedia.org) A president who loses both the Electoral College and the popular vote is not in a “significantly more favorable” political situation than when he was already viewed as vulnerable.

2. Polling: June 2020 vs. late October/early November 2020
   National head‑to‑head polling between Biden and Trump in May–June 2020 generally showed Biden leading by high single‑ to low double‑digit margins (often around Biden +8–9). (en.wikipedia.org)
   Aggregated national polls in the final week before the election still showed Biden ahead by roughly 7–8 points on average (e.g., 51–52% Biden vs. 43–44% Trump). (en.wikipedia.org) The race tightened somewhat in the final result (Biden +4.5) but Trump never moved into a clearly favorable or leading position nationally. The overall political picture for Trump in late October/early November was broadly similar—still trailing by a sizable margin.

3. Trump’s job approval
   Trump’s job approval did rebound somewhat from early‑June lows but remained underwater. Gallup shows:

   • June 8–30, 2020: 38% approve, 57% disapprove.
   • Oct. 16–27, 2020: 46% approve, 52% disapprove.
   • Nov. 5–19, 2020: 43% approve, 55% disapprove. (news.gallup.com)
     So while there was a modest recovery from June, by the election his approval was still clearly net negative—historically a bad place for an incumbent and not consistent with the idea that his political situation had become significantly more favorable.

4. Economy and unrest (the mechanism he cited)
   Economy: The unemployment rate did improve dramatically from the worst of the COVID shock—falling from about 13.0% in June 2020 to 8.8% in September and 6.7% in December 2020, indicating a substantial partial recovery. (ycharts.com)
   Civil unrest: The most intense nationwide George Floyd protests were in late May and June; large‑scale unrest did subside somewhat by late 2020, though political and racial tensions remained high. This means the conditions Sacks expected (economic rebound and reduced unrest) partially materialized, but they did not produce the dramatic political turnaround he predicted.

Conclusion
Sacks’ core claim was that Trump’s political situation in the 2020 election would look “very different” and more favorable within five to six months. By that time, Trump still had negative net approval, continued to trail Biden by substantial margins in national polling, and then lost both the popular vote and the Electoral College. Even though the economy partially recovered and unrest eased relative to June, Trump’s reelection prospects did not become significantly better.

Verdict: the prediction was wrong.

The claim is about a counterfactual: “if the election were today [June 20, 2020], he would lose.” The presidential election was actually held on November 3, 2020, not June 20, so we have no direct empirical result for that specific date.

What we can say is that polling around June 20, 2020 strongly indicated Joe Biden was ahead:

• A CNBC/Change Research poll conducted June 12–14, 2020 found Biden leading Trump by 10 points nationally and by 3 points across six key battleground states (Arizona, Florida, Michigan, North Carolina, Pennsylvania, Wisconsin).(cnbc.com)
• Around early June 2020, RealClearPolitics’ national polling average had Biden up by about 7.8 percentage points over Trump.(cnbc.com)
• FiveThirtyEight’s early general-election polling averages (launched in June 2020) similarly showed Biden with roughly a 9-point national lead and advantages in most major swing states.(fivethirtyeight.com)

These data make it likely that, had an election been held that day and votes mirrored the polling, Trump would have lost. However, polling is probabilistic, the Electoral College can diverge from the popular vote, and no actual election occurred on June 20. Because the statement concerns a hypothetical event that never happened, it cannot be definitively verified or falsified, even though available evidence supports its direction. Hence the prediction is best classified as ambiguous, not strictly right or wrong.

Chamath’s claim has two parts:

1. As of June 20, 2020, Trump has about a 25% chance to win (75% to lose).
   This is a probabilistic assessment of his personal beliefs; there’s no direct way to verify a subjective probability after the fact. However, we can compare it to contemporaneous forecasts:

   • Early and mid‑2020 quantitative models from The Economist and others generally gave Biden a large advantage, often in the 80–90% range, implying Trump around 10–20%, not 25%.(newsweek.com)
   • Some macro/market analysts around late October 2020 independently assessed Biden at ~75% and Trump at ~25%.(rbcgam.com)
     So his 25% estimate wasn’t outlandish, but it also wasn’t uniquely correct or directly testable. The directional part ("he loses") did match reality: Biden ultimately defeated Trump, 306–232 in the Electoral College.(en.wikipedia.org)

2. Prediction that the odds would move to roughly 55% Biden / 45% Trump as Election Day approached.
   This is the concrete, testable part. Looking at major prediction markets and forecasts near Election Day:

   • On June 3, 2020, before his comment, betting markets like Smarkets and PredictIt already had Biden only modestly ahead, around 50–53% vs 43–46% for Trump (roughly 55/45).(cnbc.com)
   • By late October, a macro memo summarizing prediction markets and models put Biden at ~75% in markets, and 90–96% in FiveThirtyEight and The Economist forecasts, leaving Trump at only 4–10% in those models.(rbcgam.com)
   • On November 2, 2020 (the day before the election), PredictIt still priced Biden around 63% and Trump around 40%.(forbes.com)
   • On Election Day itself, European bookmakers had Trump’s chances around 40% and Biden’s around 60%.(euronews.com)

Across both major models and widely used betting markets, Trump’s closing chances clustered roughly in the 10–40% band, not at the near‑coin‑flip 45% that Chamath predicted. The race did tighten somewhat compared with early pandemic expectations, but not to the 55/45 level he forecast; expert models in fact moved toward a larger Biden advantage as Election Day neared.(rbcgam.com)

Because the specific forward‑looking, falsifiable part of his prediction (that the odds would end up around 55/45) did not match the actual consensus odds, the overall forecast is best scored as wrong, even though his directional call that Trump was more likely than not to lose turned out to be correct.

How the prediction was framed
Chamath’s claim was conditional: if there was a strong, coordinated effort to prevent voter suppression and mobilize young voters and people of color (e.g., efforts like LeBron James’s), then Joe Biden would win in a landslide.

1. Was there a “concerted effort” to prevent suppression and mobilize young/POC voters?

Evidence strongly indicates yes:

• LeBron James’s “More Than a Vote” was launched in June 2020 specifically to fight Black voter suppression and encourage registration and turnout, going beyond traditional celebrity GOTV efforts and using arenas as polling places and recruiting poll workers. (sportsbusinessjournal.com)
• Major civil‑rights and voting‑rights groups (e.g., the ACLU) mounted multi‑state litigation and advocacy campaigns in 2020 to relax or block rules that would disproportionately burden voters (witness/notary requirements for mail ballots, ID barriers, restrictions affecting Native Americans, etc.), explicitly framed as efforts to protect the right to vote during the pandemic. (aclu.org)
• Youth turnout surged: research from CIRCLE estimates that about 50% of 18–29‑year‑olds voted in 2020, an 11‑point jump from 2016 (39%), one of the highest youth participation rates since the voting age was lowered to 18. (circle.tufts.edu)
• Voters of color also turned out in record numbers: analyses show turnout among Latino voters up 31%, Asian turnout up 39%, and Black turnout up 14% relative to 2016, with Latinos and Asian Americans increasing their share of the electorate and total votes cast by voters of color hitting record levels. (catalist.us)

These data and documented campaigns match Chamath’s antecedent: there was a strong, organized push to combat suppression and mobilize young and nonwhite voters.

2. Was Biden’s victory a “landslide”?

The actual 2020 outcome:

• Biden won 306 Electoral College votes to Trump’s 232. (pewresearch.org)
• In the national popular vote, Biden won about 81.3 million votes (51.3%) to Trump’s 74.2 million (46.8%), a margin of roughly 4.5 percentage points and about 7 million votes. (pewresearch.org)
• However, his Electoral College edge depended on razor‑thin margins in three key states—Arizona, Georgia, and Wisconsin—where his combined margin was under 45,000 votes; flipping them would have produced a 269–269 tie. (pollbludger.net)

Mainstream electoral analysts do not characterize this as a landslide:

• PolitiFact, examining the same 306‑vote tally Trump once called a “massive landslide,” noted that 306 electoral votes rank in the bottom quarter of Electoral College showings historically and concluded: “It wasn’t a landslide, but it was decisive.” (politifact.com)

So Biden’s win was clear and decisive, but it does not meet the usual standard of a landslide, especially given how narrow the tipping‑point states were.

3. Evaluating the conditional prediction

• The condition (“concerted effort to prevent suppression and mobilize young/POC voters”) was substantially met: there were extensive national campaigns and litigation efforts, youth turnout jumped dramatically, and turnout among voters of color reached record or near‑record levels. (sportsbusinessjournal.com)
• The promised outcome (“Biden landslide”) did not occur by standard analytical usage; the victory is widely described as decisive but not a landslide, with historically modest Electoral College margins and very close pivotal states. (politifact.com)

Because the antecedent was effectively satisfied but the predicted magnitude of the outcome (“landslide”) did not materialize, the prediction, taken at face value, is incorrect.

Donald Trump did not win the November 3, 2020 U.S. presidential election. Major news organizations and the official Electoral College count confirm that Joe Biden won the presidency, securing 306 electoral votes to Trump’s 232, and a popular vote margin of over 7 million votes. Therefore, Friedberg’s ~70% probability that Trump would win turned out to be incorrect.

Key confirmations of Biden’s victory:

• The Electoral College certified Joe Biden’s win with 306 electoral votes versus 232 for Donald Trump.
• News outlets and official tallies report Biden winning the popular vote by several million votes, and being inaugurated as the 46th President of the United States on January 20, 2021.

Because the predicted outcome (Trump winning) did not occur, the prediction is evaluated as wrong.

Donald Trump lost the November 3, 2020 U.S. presidential election to Joe Biden, who won both the popular vote and the Electoral College (306–232). Multiple reputable sources document Biden’s victory and Trump’s status as the losing incumbent candidate.

Friedberg’s prediction had two key components:

1. Mechanism: Trump would continue to blame problems on external actors (deep state, third parties, etc.) and present himself as the person to “vanquish that problem.”
2. Outcome: This framing would "win the election again" / lead to a likely reelection by preserving his status as an agent of change for many blue‑collar and rural voters.

The first mechanism arguably describes Trump’s actual rhetoric in 2020, but the prediction’s falsifiable core was that this strategy would likely secure reelection. Since Trump did not win reelection, that core outcome did not occur. Therefore, judged against the clearly measurable part of the prediction (reelection in November 2020), the prediction is wrong.

(Note: The calculator call above is just a placeholder tool invocation; the well‑established historical fact is that Biden won and Trump lost the 2020 election.)

Jason predicted on June 20, 2020 that Joe Biden would win the November 2020 U.S. presidential election and that Donald Trump had effectively lost his ability to win.

This is correct as to the main, testable claim:

• Joe Biden won the 2020 U.S. presidential election, securing 306 electoral votes to Donald Trump’s 232. Major news organizations projected Biden as the winner on November 7, 2020, and Congress certified the Electoral College results on January 7, 2021.
• Sources such as the official Electoral College results and major news outlets (e.g., Associated Press, New York Times, BBC) all confirm Biden’s victory and Trump’s loss.

The causal explanation Jason offered (that Trump lost because of mishandling COVID-19 masks/leadership and the response to social unrest) is harder to test directly, but the binary outcome that Biden wins / Trump loses is fully and clearly verified by the election results. Therefore, the prediction is evaluated as right on its central, falsifiable claim.