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Ranking of Harmful Industries

Below is a single, cross-sector ranking of the 16 most harmful (i.e., net-negative) industries/sectors today, blending the strongest like-for-like metrics we can get across domains: deaths/DALYs, economic costs, scale of exploitation/rights abuse, and environmental externalities. Where figures are uncertain (e.g., criminal markets), I cite the most authoritative ranges and call out caveats.

Quick note on scope: "Industries" below also includes large, persistent criminal economies (e.g., trafficking, cybercrime) when they function like industries.

Top 16 most harmful industries

1 = most harmful

1. Tobacco

  • Primary harm: massive premature mortality & morbidity from NCDs; second-hand smoke.

  • Magnitude: >7--8+ million deaths/year globally. World Health Organization+1

  • Why #1: the most consistently measured behavior-linked killer with large DALYs across all regions.

2. Alcohol

  • Primary harm: injuries (crashes, violence), cancers, liver disease; social costs.

  • Magnitude: ~2.6 million deaths/year (2019 baseline), ~4.7% of all deaths; country studies put social/economic costs ~2--3% GDP. World Health Organization+1

3.Fossil Fuels

Energy / air-pollution--intensive production

  • Primary harm: ambient + household air pollution (cardiovascular, respiratory, cancers); climate.

  • Magnitude: ~8.1 million deaths in 2021 attributable to air pollution (not all fossil---but heavily driven by it). State of Global Air

  • Why not #1: avoids double-counting household biomass; still, the public-health burden is extraordinary.

4. Ultra-processed Foods

unhealthy diet industry (incl. sugary beverages)**

  • Primary harm: diet-related NCDs (CVD, diabetes, some cancers).

  • Magnitude: ~11 million deaths (2017) attributable to dietary risks (UPFs are a major driver within this risk family). PubMed+1

5. Illicit drugs

non-medical drug trade

  • Primary harm: overdoses, blood-borne infections, violence, crime; very high DALYs.

  • Magnitude: WHO: ~0.6 million deaths/year attributed to drug use (2019); GBD/UNODC show comparable order of magnitude. World Health Organization+1

6. Sex trafficking

Forced commercial sexual exploitation (part of modern slavery)**

  • Primary harm: extreme, chronic rights abuse and trauma.

  • Magnitude: 50 million in modern slavery (any given day, 2021), 6.3 million in forced commercial sexual exploitation; ~US$236 billion/yr in illegal profits. International Labour Organization+1

7. Arms Trade

organized violent conflict ecosystem

  • Primary harm: battle and civilian deaths, displacement, destroyed health systems.

  • Magnitude: ~122,500 battle-related deaths in 2023 (UCDP); world military spend = US$2.44T (2023) → US$2.72T (2024) shows scale of the sector. SAGE Journals+2SIPRI+2

8. Cybercrime

Hackers & ransomware

  • Primary harm: large financial losses, critical-infrastructure disruption, spillover safety risks (e.g., hospital outages).

  • Magnitude: US$16.6 billion reported losses (U.S., 2024); global estimates put total cybercrime at ~US$10.5T/yr by 2025 (methodologically broad but widely cited). Internet Crime Complaint Center+2Federal Bureau of Investigation+2

9. Healthcare Fraud

  • Primary harm: diverted medical resources, delayed/denied care, patient safety risks, financial burden on healthcare systems.

  • Magnitude: US$68--230 billion/yr in the U.S. alone (National Health Care Anti-Fraud Association estimates); 3--10% of total healthcare spending globally; patient harm through unnecessary procedures and delayed legitimate care.

10. Human smuggling

Distinct from trafficking

  • Primary harm: deaths during irregular journeys; exploitation and extortion.

  • Magnitude: ~8,938 migrant deaths in 2024 (record); smuggling market ~US$5.5--7B/yr on key routes (2016 est.). International Organization for Migration+1

11. Gambling Industry

  • Primary harm: addiction, suicidality, family breakdown, crime; concentrated harms.

  • Magnitude: ~1.2% of adults meet gambling-disorder criteria worldwide; England: £1.05--£1.77 bn/yr social cost; Australia: multi-billion annual social costs. World Health Organization+2GOV.UK+2

12. Industrial livestock

factory farming

  • Primary harm: climate (methane), land-use change; antimicrobial resistance risks; severe animal-welfare harms.

  • Magnitude: ~14.5% of anthropogenic GHG from livestock supply chains (FAO baseline; newer analyses range ~12--20%). FAOHome+1

13. Deforestation and Illegal Logging

  • Primary harm: biodiversity loss, carbon emissions, Indigenous rights violations.

  • Magnitude: FAO indicates ~10 Mha/yr deforestation (2015--2020); more recent assessments show continued high loss/degradation. FAOHome+1

14. Fast Fashion

resource-intensive textile industry**

  • Primary harm: high GHG, water use/pollution, waste, labor abuses.

  • Magnitude: fashion/textiles responsible for ~2--8% of global CO₂e; ~20% of industrial wastewater (estimates vary by method). UNEP - UN Environment Programme+1

15. Crypto Industry

as a whole: bitcoin mining + on-chain ecosystem Blockchain

  • Primary harm: energy/CO₂ (primarily Bitcoin PoW), e-waste; sizable fraud/hacks externalities.

  • Magnitude: Bitcoin electricity consumption tracked by Cambridge CBECI; Ethereum's merge cut emissions by ~99.9% to the kt-scale; illicit crypto flows ≈ US$40.9B (2024) (lower-bound). ccaf.io+2Chainalysis+2

16. Pornography

(legal/adult)

  • Primary harm (to a subset): problematic use linked to mental-health/relationship issues; broader population-level harm metrics are limited/contested.

  • Magnitude: research finds PPU (problematic pornography use) in single-digit to low-double-digit % of users in some samples; no robust global mortality/economic-cost totals. PMC+1

A few framing notes

  • Apples vs. oranges: A perfect cross-domain ruler doesn't exist. I prioritized mortality/DALYs (where available), then economic costs and documented rights abuses; environmental externalities were weighted by scale and persistence.

  • Regional variation: Some harms (e.g., gambling, cybercrime) have rich national cost studies but thin global syntheses; rankings could shift under different weights (e.g., climate-only, U.S.-only).

  • Intersections: Several sectors amplify others (e.g., cybercrime ↔ crypto, deforestation ↔ livestock/feed, fossil fuels ↔ air pollution). I kept them distinct to show relative scale.

Working references (load-bearing sources)