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Engaging with AI chatbots like ChatGPT offers numerous benefits, but it’s crucial to be mindful of the information you share to safeguard your privacy. Sharing sensitive data can lead to security risks, including data breaches or unauthorized access. To protect yourself, avoid disclosing personal identity details, medical information, financial account data, proprietary corporate information, and login credentials during your interactions with ChatGPT.
Chat histories with AI tools may be stored and could potentially be accessed by unauthorized parties, especially if the AI company faces legal actions or security breaches. To mitigate these risks, it’s advisable to regularly delete your conversation history and utilize features like temporary chat modes that prevent the saving of your interactions.
Implementing strong security measures can further enhance your privacy. Use robust passwords and enable multifactor authentication for your accounts associated with AI services. These steps add layers of security, making unauthorized access more difficult.
Some AI companies, including OpenAI, provide options to manage how your data is used. For instance, you can disable model training, which prevents your conversations from being utilized to improve the AI model. Additionally, opting for temporary chats ensures that your interactions aren’t stored or used for training purposes.
For tasks involving sensitive or confidential information, consider using enterprise versions of AI tools designed with enhanced security features suitable for professional environments. These versions often come with stricter data handling policies and provide better protection for your information.
By being cautious about the information you share and utilizing available privacy features, you can enjoy the benefits of AI chatbots like ChatGPT while minimizing potential privacy risks. Staying informed about the data policies of the AI services you use and proactively managing your data sharing practices are key steps in protecting your personal and sensitive information.
Securing AI in the Enterprise: A Step-by-Step Guide
Establish AI Security Ownership Organizations must define clear ownership and accountability for AI security. Leadership should decide whether AI governance falls under a cross-functional committee, IT/security teams, or individual business units. Establishing policies, defining decision-making authority, and ensuring alignment across departments are key steps in successfully managing AI security from the start.
Identify and Mitigate AI Risks AI introduces unique risks, including regulatory compliance challenges, data privacy vulnerabilities, and algorithmic biases. Organizations must evaluate legal obligations (such as GDPR, HIPAA, and the EU AI Act), implement strong data protection measures, and address AI transparency concerns. Risk mitigation strategies should include continuous monitoring, security testing, clear governance policies, and incident response plans.
Adopt AI Security Best Practices Businesses should follow security best practices, such as starting with small AI implementations, maintaining human oversight, establishing technical guardrails, and deploying continuous monitoring. Strong cybersecurity measures—such as encryption, access controls, and regular security audits—are essential. Additionally, comprehensive employee training programs help ensure responsible AI usage.
Assess AI Needs and Set Measurable Goals AI implementation should align with business objectives, with clear milestones set for six months, one year, and beyond. Organizations should define success using key performance indicators (KPIs) such as revenue impact, efficiency improvements, and compliance adherence. Both quantitative and qualitative metrics should guide AI investments and decision-making.
Evaluate AI Tools and Security Measures When selecting AI tools, organizations must assess security, accuracy, scalability, usability, and compliance. AI solutions should have strong data protection mechanisms, clear ROI, and effective customization options. Evaluating AI tools using a structured approach ensures they meet security and business requirements.
Purchase and Implement AI Securely Before deploying AI solutions, businesses must ask key questions about effectiveness, performance, security, scalability, and compliance. Reviewing trial options, pricing models, and regulatory alignment (such as GDPR or CCPA compliance) is critical to selecting the right AI tool. AI security policies should be integrated into the organization’s broader cybersecurity framework.
Launch an AI Pilot Program with Security in Mind Organizations should begin with a controlled AI pilot to assess risks, validate performance, and ensure compliance before full deployment. This includes securing high-quality training data, implementing robust authentication controls, continuously monitoring performance, and gathering user feedback. Clear documentation and risk management strategies will help refine AI adoption in a secure and scalable manner.
By following these steps, enterprises can securely integrate AI, protect sensitive data, and ensure regulatory compliance while maximizing AI’s potential.
Amid the rush to adopt AI, leaders face significant risks if they lack an understanding of the technology’s potential cyber threats. A PwC survey revealed that 40% of global leaders are unaware of generative AI’s risks, posing potential vulnerabilities. CISOs should take a leading role in assessing, implementing, and overseeing AI, as their expertise in risk management can ensure safer integration and focus on AI’s benefits. While some advocate for a chief AI officer, security remains integral, emphasizing the CISO’s/ vCISO’S strategic role in guiding responsible AI adoption.
CISOs are crucial in managing the security and compliance of AI adoption within organizations, especially with evolving regulations. Their role involves implementing a security-first approach and risk management strategies, which includes aligning AI goals through an AI consortium, collaborating with cybersecurity teams, and creating protective guardrails.
They guide acceptable risk tolerance, manage governance, and set controls for AI use. Whether securing AI consumption or developing solutions, CISOs must stay updated on AI risks and deploy relevant resources.
A strong security foundation is essential, involving comprehensive encryption, data protection, and adherence to regulations like the EU AI Act. CISOs enable informed cross-functional collaboration, ensuring robust monitoring and swift responses to potential threats.
As AI becomes mainstream, organizations must integrate security throughout the AI lifecycle to guard against GenAI-driven cyber threats, such as social engineering and exploitation of vulnerabilities. This requires proactive measures and ongoing workforce awareness to counter these challenges effectively.
“AI will touch every business function, even in ways that have yet to be predicted. As the bridge between security efforts and business goals, CISOs serve as gatekeepers for quality control and responsible AI use across the business. They can articulate the necessary ground for security integrations that avoid missteps in AI adoption and enable businesses to unlock AI’s full potential to drive better, more informed business outcomes. “
CISOs play a pivotal role in guiding responsible AI adoption to balance innovation with security and compliance. They need to implement security-first strategies and align AI goals with organizational risk tolerance through stakeholder collaboration and robust risk management frameworks. By integrating security throughout the AI lifecycle, CISOs/vCISOs help protect critical assets, adhere to regulations, and mitigate threats posed by GenAI. Vigilance against AI-driven attacks and fostering cross-functional cooperation ensures that organizations are prepared to address emerging risks and foster safe, strategic AI use.
Need expert guidance? Book a free 30-minute consultation with a vCISO.
How do you solve privacy issues with AI? It’s all about the blockchain
Data is the lifeblood of artificial intelligence (AI), and the power that AI brings to the business world — to unearth fresh insights, increase speed and efficiency, and multiply effectiveness — flows from its ability to analyze and learn from data. The more data AI has to work with, the more reliable its results will be.
Feeding AI’s need for data means collecting it from a wide variety of sources, which has raised concerns about AI gathering, processing, and storing personal data. The fear is that the ocean of data flowing into AI engines is not properly safeguarded.
Are you donating your personal data to generative AI platforms?
While protecting the data that AI tools like ChatGPT is collecting against breaches is a valid concern, it is actually only the tip of the iceberg when it comes to AI-related privacy issues. A more poignant issue is data ownership. Once you share information with a generative AI tool like Bard, who owns it?
Those who are simply using generative AI platforms to help craft better social posts may not understand the connection between the services they offer and personal data security. But consider the person who is using an AI-driven chatbot to explore treatment for a medical condition, learn about remedies for a financial crisis, or find a lawyer. In the course of the exchange, those users will most likely share some personal and sensitive information.
Every query posed to an AI platform becomes part of that platform’s data set without regard to whether or not it is personal or sensitive. ChatGPT’s privacy policy makes it clear: “When you use our Services, we collect Personal Information that is included in the input, file uploads, or feedback that you provide to our Services.” It also says: “In certain circumstances we may provide your Personal Information to third parties without further notice to you, unless required by the law…”
Looking to blockchain for data privacy solutions
While the US government has called for an “AI Bill of Rights” designed to protect sensitive data, it has yet to provide the type of regulations that protect its ownership. Consequently, Google and Microsoft have full ownership over the data that their users provide as they comb the web with generative AI platforms. That data empowers them to train their AI models, but also to get to understand you better.
Those looking for a way to gain control of their data in the age of AI can find a solution in blockchain technology. Commonly known as the foundation of cryptocurrency, blockchain can also be used to allow users to keep their personal data safe. By empowering a new type of digital identity management — known as a universal identity layer — blockchain allows you to decide how and when your personal data is shared.
Blockchain technology brings a number of factors into play that boost the security of personal data. First, it is decentralized, meaning that data is not stored in a centralized database and is not subject to its vulnerabilities with blockchain.
Blockchain also supports smart contracts, which are self-executing contracts that have the terms of an agreement written into their code. If the terms aren’t met, the contract does not execute, allowing for data stored on the blockchain to be utilized only in the way in which the owner stipulates.
Enhanced security is another factor that blockchain brings to data security efforts. The cryptographic techniques it utilizes allow users to authenticate their identity without revealing sensitive data.
Leveraging these factors to create a new type of identification framework gives users full control of who can use and view their information, for what purposes, and for how long. Once in place, this type of identity system could even be used to allow users to monetize their data, charging large language models (LLMs) like OpenAI and Google Bard to benefit from the use of personal data.
Ultimately, AI’s ongoing needs may lead to the creation of platforms where users offer their data to LLMs for a fee. A blockchain-based universal identity layer would allow the user to choose who gets to use it, toggling access on and off at will. If you decide you don’t like the business practices Google has been employing over the past two months, you can cut them off at the source.
That type of AI model illustrates the power that comes from securing data on a decentralized network. It also reveals the killer use case of blockchain that is on the horizon.
Aaron Rafferty is the CEO of Standard DAO and Co-Founder of BattlePACs, a subsidiary of Standard DAO. BattlePACs is a technology platform that transforms how citizens engage in politics and civil discourse. BattlePACs believes participation and conversations are critical to moving America toward a future that works for everyone.
