{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T23:23:11Z","timestamp":1770160991960,"version":"3.49.0"},"reference-count":39,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Generative AI (GenAI) now produces text, images, audio, and video that can be perceptually convincing at scale and at negligible marginal cost. While public debate often frames the associated harms as \u201cdeepfakes\u201d or incremental extensions of misinformation and fraud, this view misses a broader socio-technical shift: GenAI enables synthetic realities\u2014coherent, interactive, and potentially personalized information environments in which content, identity, and social interaction are jointly manufactured and mutually reinforcing. We argue that the most consequential risk is not merely the production of isolated synthetic artifacts, but the progressive erosion of shared epistemic ground and institutional verification practices as synthetic content, synthetic identity, and synthetic interaction become easy to generate and hard to audit. This paper (i) formalizes synthetic reality as a layered stack (content, identity, interaction, institutions), (ii) expands a taxonomy of GenAI harms spanning personal, economic, informational, and socio-technical risks, (iii) articulates the qualitative shifts introduced by GenAI (cost collapse, throughput, customization, micro-segmentation, provenance gaps, and trust erosion), and (iv) synthesizes recent risk realizations (2023\u20132025) into a compact case bank illustrating how these mechanisms manifest in fraud, elections, harassment, documentation, and supply-chain compromise. We then propose a mitigation stack that treats provenance infrastructure, platform governance, institutional workflow redesign, and public resilience as complementary rather than substitutable, and outline a research agenda focused on measuring epistemic security. We conclude with the Generative AI Paradox: as synthetic media becomes ubiquitous, societies may rationally discount digital evidence altogether, raising the cost of truth for everyday life and for democratic and economic institutions.<\/jats:p>","DOI":"10.3390\/fi18020073","type":"journal-article","created":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T10:03:29Z","timestamp":1770113009000},"page":"73","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Generative AI Paradox: GenAI and the Erosion of Trust, the Corrosion of Information Verification, and the Demise of Truth"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1942-2831","authenticated-orcid":false,"given":"Emilio","family":"Ferrara","sequence":"first","affiliation":[{"name":"Thomas Lord Department of Computer Science, University of Southern California (USC), Los Angeles, CA 90089, USA"},{"name":"Annenberg School for Communication, University of Southern California (USC), Los Angeles, CA 90089, USA"},{"name":"Information Sciences Institute (ISI), University of Southern California (USC), Marina del Rey, CA 90089, USA"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,1]]},"reference":[{"key":"ref_1","unstructured":"California Government Operations Agency (2026, January 22). State of California: Benefits and Risks of Generative Artificial Intelligence Report, Available online: https:\/\/www.govops.ca.gov\/wp-content\/uploads\/sites\/11\/2023\/11\/GenAI-EO-1-Report_FINAL.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Eapen, T.T., Finkenstadt, D.J., Folk, J., and Venkataswamy, L. (2026, January 22). How Generative AI Can Augment Human Creativity. Available online: https:\/\/hbr.org\/2023\/07\/how-generative-ai-can-augment-human-creativity.","DOI":"10.2139\/ssrn.4759930"},{"key":"ref_3","unstructured":"NPR (2026, January 22). AI Images of Hurricanes and Other Disasters Are Flooding Social Media. Available online: https:\/\/www.npr.org\/2024\/10\/18\/nx-s1-5153741\/ai-images-hurricanes-disasters-propaganda."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1007\/s42001-024-00250-1","article-title":"GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Models","volume":"7","author":"Ferrara","year":"2024","journal-title":"J. Comput. Soc. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1038\/s42256-023-00690-w","article-title":"Addressing the harms of AI-generated inauthentic content","volume":"5","author":"Menczer","year":"2023","journal-title":"Nat. Mach. Intell."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1145\/3584973","article-title":"Beyond Deep Fakes","volume":"66","author":"Seymour","year":"2023","journal-title":"Commun. ACM"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1145\/3624721","article-title":"Disinformation 2.0 in the Age of AI: A Cybersecurity Perspective","volume":"67","author":"Mazurczyk","year":"2024","journal-title":"Commun. ACM"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ferrara, E. (2025). Charting the landscape of nefarious uses of generative artificial intelligence for online election interference. First Monday, 30.","DOI":"10.5210\/fm.v30i6.14188"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Minici, M., Cinus, F., Luceri, L., and Ferrara, E. (2024). Uncovering coordinated cross-platform information operations: Threatening the integrity of the 2024 U.S. presidential election. First Monday, 29.","DOI":"10.5210\/fm.v29i11.13831"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Cinus, F., Minici, M., Luceri, L., and Ferrara, E. (May, January 28). Exposing cross-platform coordinated inauthentic activity in the run-up to the 2024 us election. Proceedings of the ACM on Web Conference 2025, Sydney, NSW, Australia.","DOI":"10.2139\/ssrn.5018877"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1038\/s42256-024-00881-z","article-title":"Factuality challenges in the era of large language models and opportunities for fact-checking","volume":"6","author":"Augenstein","year":"2024","journal-title":"Nat. Mach. Intell."},{"key":"ref_12","unstructured":"Augenstein, I., Bakker, M., Chakraborty, T., Corney, D., Ferrara, E., Gurevych, I., Hale, S., Hovy, E., Ji, H., and Larraz, I. (2025). Community Moderation and the New Epistemology of Fact Checking on Social Media. arXiv."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ferrara, E. (2023). Social bot detection in the age of ChatGPT: Challenges and opportunities. First Monday, 28.","DOI":"10.5210\/fm.v28i6.13185"},{"key":"ref_14","unstructured":"Government of the Hong Kong Special Administrative Region (2026, January 22). LCQ9: Combating Frauds Involving Deepfake, Available online: https:\/\/www.info.gov.hk\/gia\/general\/202406\/26\/P2024062600192p.htm."},{"key":"ref_15","unstructured":"Financial Times (2026, January 22). Arup Lost $25 mn in Hong Kong Deepfake Video Conference Scam. Available online: https:\/\/www.ft.com\/content\/b977e8d4-664c-4ae4-8a8e-eb93bdf785ea."},{"key":"ref_16","unstructured":"South China Morning Post (2026, January 22). Hong Kong Employee Tricked into Paying out HK$4 Million After Video Call with Deepfake \u2018CFO\u2019 of UK Multinational Firm. Available online: https:\/\/www.scmp.com\/news\/hong-kong\/law-and-crime\/article\/3263151\/uk-multinational-arup-confirmed-victim-hk200-million-deepfake-scam-used-digital-version-cfo-dupe."},{"key":"ref_17","unstructured":"Federal Communications Commission (2026, January 22). DA 24-102: Robocall Enforcement (Public Notice; Cease-and-Desist to Lingo Telecom Re: AI-Generated Voice), Available online: https:\/\/docs.fcc.gov\/public\/attachments\/DA-24-102A1.pdf."},{"key":"ref_18","unstructured":"Associated Press (2026, January 22). AI-Generated Voices in Robocalls Can Deceive Voters. The FCC Just Made Them Illegal. Available online: https:\/\/apnews.com\/article\/a8292b1371b3764916461f60660b93e6."},{"key":"ref_19","unstructured":"NPR (2026, January 22). A Political Consultant Faces Charges and Fines for Biden Deepfake Robocalls. Available online: https:\/\/www.npr.org\/2024\/05\/23\/nx-s1-4977582\/fcc-ai-deepfake-robocall-biden-new-hampshire-political-operative."},{"key":"ref_20","unstructured":"Associated Press (2026, January 22). X Restores Taylor Swift Searches After Deepfake Explicit Images Triggered Temporary Block. Available online: https:\/\/apnews.com\/article\/adec3135afb1c6e5363c4e5dea1b7a72."},{"key":"ref_21","unstructured":"WIRED (2026, January 22). GitHub\u2019s Deepfake Porn Crackdown Still Isn\u2019t Working. Available online: https:\/\/www.wired.com\/story\/githubs-deepfake-porn-crackdown-still-isnt-working."},{"key":"ref_22","unstructured":"Congressional Research Service (2026, January 22). The TAKE IT DOWN Act: A Federal Law Prohibiting the Nonconsensual Publication of Intimate Images, Available online: https:\/\/www.congress.gov\/crs-product\/LSB11314."},{"key":"ref_23","unstructured":"Associated Press (2026, January 22). President Trump Signs Take It Down Act, Addressing Nonconsensual Deepfakes. What Is It? 2025. Available online: https:\/\/apnews.com\/article\/741a6e525e81e5e3d8843aac20de8615."},{"key":"ref_24","unstructured":"Financial Times (2026, January 22). \u2018Do not Trust Your Eyes\u2019: AI Generates Surge in Expense Fraud. Available online: https:\/\/www.ft.com\/content\/0849f8fe-2674-4eae-a134-587340829a58."},{"key":"ref_25","unstructured":"SAP Concur (2026, January 22). Fake Receipts 2.0: Why Human Audits Fail Against AI and How Tech Is Fighting Back. Available online: https:\/\/www.concur.com\/blog\/article\/fake-receipts-20-why-human-audits-fail-against-ai-and-how-tech-is-fighting-back."},{"key":"ref_26","unstructured":"ICAEW (2026, January 22). Expenses Fraud: How to Spot an AI-Generated Receipt. Available online: https:\/\/www.icaew.com\/insights\/viewpoints-on-the-news\/2025\/nov-2025\/expenses-fraud-how-to-spot-an-ai-generated-receipt."},{"key":"ref_27","unstructured":"PYMNTS (2026, January 22). Ramp Adds AI Agents for Invoice Processing. Available online: https:\/\/www.pymnts.com\/news\/artificial-intelligence\/2025\/ramp-adds-ai-agents-invoice-coding-approval-payment-processing\/."},{"key":"ref_28","unstructured":"Financial Times (2026, January 22). Fraudsters Use AI to Fake Artwork Authenticity and Ownership. Available online: https:\/\/www.ft.com\/content\/fdfb5489-daa0-4e7e-97b7-4317514cd9f4."},{"key":"ref_29","unstructured":"Autio, C., Schwartz, R., Dunietz, J., Jain, S., Stanley, M., Tabassi, E., Hall, P., and Roberts, K. (2026, January 22). Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, Available online: https:\/\/www.nist.gov\/publications\/artificial-intelligence-risk-management-framework-generative-artificial-intelligence."},{"key":"ref_30","unstructured":"GitHub Advisory Database (2026, January 22). PyTorch Model Files Can Bypass Pickle Scanners via Unexpected Pickle Extensions (CVE-2025-1889). Available online: https:\/\/github.com\/advisories\/GHSA-769v-p64c-89pr."},{"key":"ref_31","unstructured":"OWASP GenAI Security Project (2026, January 22). OWASP Gen AI Incident & Exploit Round-Up, Jan\u2013Feb 2025 (nullifAI Malicious Models on Hugging Face Hub). Available online: https:\/\/genai.owasp.org\/2025\/03\/06\/owasp-gen-ai-incident-exploit-round-up-jan-feb-2025\/."},{"key":"ref_32","unstructured":"Hubinger, E., Denison, C., Mu, J., Lambert, M., Tong, M., MacDiarmid, M., Lanham, T., Ziegler, D.M., Maxwell, T., and Cheng, N. (2024). Sleeper agents: Training deceptive llms that persist through safety training. arXiv."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"He, P., Xu, H., Xing, Y., Liu, H., Yamada, M., and Tang, J. (May, January 29). Data Poisoning for In-context Learning. Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, NM, USA.","DOI":"10.18653\/v1\/2025.findings-naacl.91"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Chen, Z., Ye, J., Tsai, B., Ferrara, E., and Luceri, L. (2025, January 15\u201319). Synthetic politics: Prevalence, spreaders, and emotional reception of AI-generated political images on X. Proceedings of the 36th ACM Conference on Hypertext and Social Media, Chicago, IL, USA.","DOI":"10.1145\/3720553.3746675"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Ye, J., Luceri, L., and Ferrara, E. (2025, January 23\u201326). Auditing Political Exposure Bias: Algorithmic Amplification on Twitter\/X During the 2024 US Presidential Election. Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, Athens, Greece.","DOI":"10.1145\/3715275.3732159"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3610061","article-title":"Examining the impact of provenance-enabled media on trust and accuracy perceptions","volume":"7","author":"Feng","year":"2023","journal-title":"Proc. ACM-Hum.-Comput. Interact."},{"key":"ref_37","unstructured":"Luceri, L., Salkar, T.V., Balasubramanian, A., Pinto, G., Sun, C., and Ferrara, E. (2026, January 27\u201329). Coordinated Inauthentic Behavior on TikTok: Challenges and Opportunities for Detection in a Video-First Ecosystem. Proceedings of the International AAAI Conference on Web and Social Media, Los Angeles, CA, USA."},{"key":"ref_38","unstructured":"European Institute for Gender Equality (2022). Combating Cyber Violence Against Women and Girls, European Institute for Gender Equality (EIGE). Available online: https:\/\/eige.europa.eu\/sites\/default\/files\/documents\/combating_cyber_violence_against_women_and_girls.pdf."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ferrara, E. (2024). Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6.","DOI":"10.2196\/preprints.48399"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/2\/73\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T10:13:32Z","timestamp":1770113612000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/2\/73"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,1]]},"references-count":39,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["fi18020073"],"URL":"https:\/\/doi.org\/10.3390\/fi18020073","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,1]]}}}