AI Must Learn From Crypto’s Mistakes to Win Public Trust #CriptoNews

Artificial intelligence is rapidly becoming the most transformative technology of our time. Yet, as it surpasses other cutting-edge innovations like cryptocurrency and blockchain in the public consciousness, it is also acquiring an unenviable reputation. Despite its astounding progress and immense promise, AI is now vying for the dubious distinction of being one of the most mistrusted industries.

From fears of AI-generated deepfakes spreading political disinformation to tragic stories of chatbots linked to self-harm, the public narrative around AI seems increasingly negative. Whether it’s headlines about a fabricated Taylor Swift endorsement misleading fans or an AI chatbot allegedly pushing a teenager to kill himself, these incidents fuel anxieties about a technology that could spiral out of control.

The AI industry faces an image problem that echoes the challenges previously encountered by the cryptocurrency sector. To navigate this critical juncture, AI innovators must learn from crypto’s missteps in communication and public engagement to build trust and ensure responsible innovation.

Artificial intelligence and cryptocurrency each have the potential to redefine industries, economies and personal experiences. But they share a common challenge: significant reputational issues stemming from public fear, misuse and regulatory scrutiny. As someone who has spent years working with tech startups in both AI and blockchain, I’ve witnessed firsthand how miscommunication and a lack of proactive engagement can stall even the most groundbreaking innovations.

The crypto industry, in particular, has navigated a tumultuous journey—from the heights of speculative excitement to the depths of public disillusionment and stringent regulations. The growing concerns over AI’s impact on society, exemplified by high-profile cases of misuse, offer a timely parallel. AI startups can choose to either repeat crypto’s mistakes or forge a path that fosters trust and emphasizes ethical responsibility.

Shared Reputational Challenges

Cryptocurrency’s early days were marred by stories of fraud, volatility and associations with illicit activities. High-profile hacks and scams overshadowed the transformative potential of blockchain technology in areas like secure data sharing and financial inclusion.

AI now faces its own set of challenges. On the eve of the U.S. election, fears of AI-generated deepfakes have raised alarms about the erosion of truth, and the manipulation of public opinion and worries over AI chatbot characters have intensified concerns about the ethical design and deployment of AI systems. There is apprehension that AI could inadvertently cause harm if it’s not properly regulated and monitored.

Regulators and lawmakers are taking notice. Discussions about implementing guidelines and laws to govern AI technologies are gaining momentum worldwide. Without proactive engagement and effective communication, AI companies risk being hampered by regulations that could stifle innovation and delay the deployment of beneficial technologies.

Unlike the crypto industry, governments are eager to harness the potential of AI for national security and economic competitiveness. The White House issued a memo this month emphasizing the importance of AI in national security and directed federal agencies to adopt AI technologies while prioritizing safety, security and trustworthiness. This governmental appetite for AI progress provides the industry with a unique opportunity to manage its reputation effectively and collaborate with policymakers to accelerate responsible adoption in contrast to the crypto sector, which faced years of often hostile resistance.

One critical mistake made by many crypto projects was overpromising and under-delivering. Grand visions were laid out, but tangible products or services often failed to materialize. This gap between expectation and reality led to public disillusionment and increased regulatory scrutiny.

AI startups must avoid this pitfall by focusing on practical, real-world applications that prioritize safety and ethical considerations. For instance, developers should implement robust safeguards in AI systems to prevent misuse and unintended consequences. By demonstrating a commitment to user well-being and ethical standards, companies can build trust and credibility.

Effective Communication, Ethical Responsibility

Communication is more than marketing; it’s about building relationships and fostering understanding. The crypto industry often struggled with opaque messaging and a lack of transparency, which fueled mistrust.

AI startups should take a different approach:

• Transparency: Be open about how AI systems work, the data they use and their limitations. Transparency demystifies the technology and alleviates fears stemming from the “black box” nature of some AI models.
• Ethical guidelines: Develop and adhere to strict ethical guidelines regarding the use and deployment of AI. Publicly sharing these guidelines can build trust and set industry standards.
• Proactive engagement: Don’t wait for regulations to be imposed. Engage with policymakers, the public and other stakeholders to shape sensible regulations that protect society without hindering innovation.

Building Bridges With Stakeholders

Crypto’s adversarial stance toward regulators and traditional institutions often backfired. In contrast, AI startups should aim to collaborate:

• Work with regulators: Establish open lines of communication with lawmakers to inform them about the technology and its implications. Offering expertise can help craft balanced policies that protect users while allowing innovation to flourish.
• Educate the public: Invest in public education initiatives to improve understanding of AI. This could involve community workshops, informative content or partnerships with educational institutions.
• Collaborate with experts: Engage with ethicists, psychologists and other professionals to ensure AI systems are designed with a holistic understanding of human behavior and societal impact.

The Convergence of AI and Crypto

Interestingly, AI and crypto are not just parallel technologies but increasingly intersecting ones. Blockchain technology can offer solutions to some of AI’s challenges:

• Data integrity and privacy: Blockchain can enhance data security and give users control over their personal information, addressing privacy concerns inherent in AI data collection practices.
• Authenticity verification: Blockchain can help verify the authenticity of digital content, providing a defense against deepfakes by creating immutable records of original media.
• Decentralized compute power: Decentralized networks can distribute computational resources across multiple nodes, enabling the training of AI models on massive datasets without relying on centralized data centers. This approach reduces costs, enhances efficiency and democratizes access to AI development by allowing a broader range of participants to contribute processing power and collaborate on AI innovations.

Learning From Crypto’s Experience

Crypto’s turbulent history provides a road map of pitfalls to avoid:

• Avoid complacency: Recognize that public trust must be earned and maintained through consistent action and communication.
• Address misuse proactively: Just as crypto faced issues with illicit activities, AI must tackle the potential for misuse head-on, developing safeguards against harmful applications like deepfakes or unethical chatbots.
• Demonstrate social responsibility: Companies that show a commitment to societal well-being can differentiate themselves and build stronger relationships with both the public and regulators.

Addressing Impact on Society

Both AI and crypto have the potential to disrupt societal norms and institutions. This disruption can lead to resistance unless managed thoughtfully:

• Mitigate negative impacts: Actively work to reduce potential harms, such as mental health risks or the erosion of trust in information.
• Highlight positive contributions: Emphasize how AI can enhance lives, from improving health care outcomes to enabling new forms of communication and education.
• Foster inclusivity: Ensure that AI technologies are developed with diverse perspectives to serve a broad range of communities fairly.

Conclusion

The drumbeat of negative headlines about AI underscores the urgent need for the industry to address its image problem. By learning from the crypto industry’s missteps—overpromising, poor communication and adversarial stances—AI companies can navigate these challenges more effectively.

Effective communication, ethical responsibility and proactive engagement are not just strategies for success; they are necessities. The goal is not just technological advancement but integrating innovation into society in a way that is accepted and trusted.

AI has the chance to write a different story—a story where technology and humanity advance together, responsibly and ethically. By addressing fears, demonstrating real value and committing to ethical practices, AI startups can ensure that they are part of the solution, not the problem.

Saul Hudson is a managing partner at Angle42a strategic communications agency for fast-growing startups in the Web3, AI and emerging technology industries.