How to Detect Fakes During Global Unrest Using AI and Blockchain - InformationWeek

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IoT
IoT
Data Management // AI/Machine Learning
Commentary
7/13/2020
07:00 AM
Avivah Litan, VP, Distinguished Analyst, Gartner Inc.
Avivah Litan, VP, Distinguished Analyst, Gartner Inc.
Commentary
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How to Detect Fakes During Global Unrest Using AI and Blockchain

Until the next technical evolution, current blockchain and AI/ML applications will continue to raise the trustworthiness bar in our zero-trust world.

Detecting fakes -- or altered or illegitimate representations of the truth -- is more important than ever during this period of global and civil unrest that we find ourselves in. Counterfeiters have leveraged consumer fear and uncertainty created by coronavirus (COVID-19) to flood the market with fakes, misinformation and counterfeits, taking advantage of demand and panic buying for essential goods and services.

Image: klss777 - stock.adobe.com
Image: klss777 - stock.adobe.com

As one example, social media bot accounts are causing life-threatening coronavirus misinformation to spread across the internet. The Reuters Institute for the Study of Journalism and the Oxford Internet Institute recently released the results of a study that reviewed 225 pieces of COVID-19 misinformation rated false or misleading by fact-checkers. The research found that “false (COVID-19) information spread by politicians, celebrities, and other prominent public figures” accounted for 69% of total engagement on social media, even though their posts made up just 20% of the study’s sample.

Likewise, counterfeit N95 masks, test kits and ventilator parts have posed challenges for governments across the globe trying to keep their populations safe during COVID-19. Taken together, the reality of fakes during this global pandemic led the World Health Organization’s Director-General Tedros Ghebreyesus to state in February: “We’re not just fighting an epidemic; we’re fighting an infodemic.”

The presence of “fake everything” has intensified in the last five months alone, which shows a grim outlook for what’s ahead. While there are no aggregate numbers on the economic costs of disinformation, forged identities, impersonation and other forms of fake entities to date, fakes undermine and damage key public figures and organizations.

Enterprises must ensure the integrity and authenticity of their supply chains and ecosystems to maintain revenue, business value, and brand reputation. Yet service providers, government regulators and digital giants are far behind where they need to be in solving the problem of “fakes” and distorted reality for organizations that rely on their services.

Technology’s role in combatting ‘fake everything’

Despite the threat that “fake everything” poses to our democracy and society as a whole, there are promising signs that it can be solved in part by technologies that support security and safety, such as artificial intelligence, machine learning and blockchain.

Blockchain, for instance, is anticipated to help authenticate over 5% of worldwide news and video content as real by 2023, with major news and domestic organizations leveraging blockchain technology to do so as early as next year. Blockchain uniquely supports trust in the supply chain and asset tracking, trust in the provenance of digital assets and physical goods, and trust in the identifies of providers, consumers, businesses and “things,” among other benefits.

Several organizations are working to develop software programs that can identify and “blacklist” fake content so that it can be blocked from reaching target victims. A complementary and probably more effective method for stopping fake news and content dissemination uses a “whitelisting” approach that authenticates and tracks content movement, ensuring its provenance. Blockchain technology excels at supporting this use case because it enables a “shared single version of truth” across multiple entities based on immutable data and audit trails. Tracking assets and proving provenance are two key successful use cases for permissioned blockchain and can be readily applied to tracking the provenance of news content.

Near-term action plan for fighting fakes

Although combatting fakes will be amplified and assisted through technological advances and regulatory oversight in the future, the million-dollar question still persists: “How do I know if this entity is real?” Enterprise IT leaders must get started on an action plan now.

First, develop a risk-based, pragmatic approach to fighting fakes. Highlight the trust gaps in your organization’s systems and processes. Evaluate its ability (or inability) to cope in a trustless environment and the impact on the organization’s standing or brand. Work with business units to identify current challenges with fakes, either as an originator or recipient of fake goods or content.

Develop a plan to address the identified problems using the Gartner Model for Truth Assessment, which analyzes entities in an integrated and ongoing fashion. The model consists of four “shades” of truth: known good, likely good, known bad, likely bad. Human verification, algorithmic verification or digital certification -- or some combination of these techniques -- is used to determine where an entity falls on the model. This helps systematically weed out fake entities from the real thing while saving money and promoting human safety and trust.

Map your project priorities to available tools, verification and certification techniques, and stay abreast of industry developments to upgrade your solution set as needed. Emulate leading organizations and use leading edge, domain-specific solutions that leverage AI models for fakes detection, DNA or spectral imaging analysis where available for provenance certification, and blockchain tracking for provenance assurance.

Finally, work with peers to identify and implement best practices. It is paramount to participate in working groups and industry consortia to develop the applications and processes for effective content provenance tracking. Seek out peers that are also working on the problem of fakes to leverage best practices and pragmatic near-term steps.

The future of fighting fakes

In the short term, there is no doubt that IT leaders must use the tools and methods they presently have at their disposal to combat the threat. However, over the next 5-10 years, Gartner expects technical, organizational and regulatory evolution of fake detection, leading to certified third-party truth assessments from which everyone can benefit. Until then, blockchain and AI/ML applications will certainly raise the trustworthiness bar in our zero-trust world, which is desperately needed during this crisis.

Avivah Litan is a Vice President and Distinguished Analyst in Gartner Research. Litan is currently managing the Gartner research agenda for Application Leaders across the Application's group. She is also a member of the ITL Application Innovation team that covers blockchain, AI and IoT. She specializes in AI security, and also blockchain innovation and technology. Read her blog here.

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