Jan 27
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Naz
Testing LLM for Data Privacy
Test if chatgpt stores your data
As someone who frequently uses ChatGPT and other LLM-based AI tools, I've become a keen observer of their impact on our digital lives. These tools are invaluable to me as a knowledge worker with an insatiable thirst for information. However, I'm acutely aware of the privacy risks involved. I regularly conduct my own tests to gauge their safety - though these are basic, they're a solid starting point.
Decoding LLMs: In this digital epoch, LLMs like GPT-4 are redefining our interaction with AI. They're a beacon of progress, enhancing efficiency and creativity across various sectors, from enhancing customer support to enriching content creation. Yet, they carry a double-edged sword.
The Privacy Conundrum: The crux of the issue lies in the data these models train on, which often contains sensitive details. This sparks significant concerns about user privacy and data security. The big question is: how do we harness the power of LLMs while safeguarding our personal data?
Adopting Best Practices in Data Privacy:
1. Transparency: Firms need to openly communicate about the data they collect and its usage. Users deserve to understand what they're signing up for.
2. Consent: It's imperative to obtain explicit consent, particularly for sensitive data.
3. Data Anonymization: Stripping datasets of identifiable information is a key step in preserving privacy.
4. Regulatory Adherence: Following data protection regulations like GDPR and CCPA is non-negotiable.
5. Ongoing Vigilance: Regular reviews and updates are essential to stay aligned with privacy norms and tackle new challenges.
Tips for Standard Users to Protect Privacy:
1. Be Cautious with Personal Information: Avoid sharing sensitive personal details like your address, phone number, or financial information.
2. Review Privacy Policies: Take the time to read and understand the privacy policies of the LLM tools you use.
3. Use Secure Networks: Access LLM tools through secure, private networks rather than public Wi-Fi.
4. Keep Software Updated: Regular updates often include security enhancements.
5. Utilize Privacy Settings: Adjust the privacy settings within the tools to control what data you share and how it's used.
Charting the Path Ahead: Adopting LLMs demands a nuanced approach. We need to balance their incredible potential against the imperative of protecting data privacy. It's not merely about legal compliance; it's about fostering and upholding the trust of users.
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Ali Hessami is currently the Director of R&D and Innovation at Vega Systems, London, UK. He has an extensive track record in systems assurance and safety, security, sustainability, knowledge assessment/management methodologies. He has a background in the design and development of advanced control systems for business and safety-critical industrial applications.
Hessami represents the UK on the European Committee for Electrotechnical Standardization (CENELEC) & International Electrotechnical Commission (IEC) – safety systems, hardware & software standards committees. He was appointed by CENELEC as convener of several Working Groups for review of EN50128 Safety-Critical Software Standard and update and restructuring of the software, hardware, and system safety standards in CENELEC.
Ali is also a member of Cyber Security Standardisation SGA16, SG24, and WG26 Groups and started and chairs the IEEE Special Interest Group in Humanitarian Technologies and the Systems Council Chapters in the UK and Ireland Section. In 2017 Ali joined the IEEE Standards Association (SA), initially as a committee member for the new landmark IEEE 7000 standard focused on “Addressing Ethical Concerns in System Design.” He was subsequently appointed as the Technical Editor and later the Chair of P7000 working group. In November 2018, he was appointed as the VC and Process Architect of the IEEE’s global Ethics Certification Programme for Autonomous & Intelligent Systems (ECPAIS).
Trish advises and trains organisations internationally on Responsible AI (AI/data ethics, policy, governance), and Corporate Digital Responsibility.
Patricia has 20 years’ experience as a lawyer in data, technology and regulatory/government affairs and is a registered Solicitor in England and Wales, and the Republic of Ireland. She has authored and edited several works on law and regulation, policy, ethics, and AI.
She is an expert advisor on the Ethics Committee to the UK’s Digital Catapult Machine Intelligence Garage working with AI startups, is a Maestro (a title only given to 3 people in the world) and expert advisor “Maestro” on the IEEE’s CertifAIEd (previously known as ECPAIS) ethical certification panel, sits on IEEE’s P7003 (algorithmic bias)/P2247.4 (adaptive instructional systems)/P7010.1 (AI and ESG/UN SDGS) standards programmes, is a ForHumanity Fellow working on Independent Audit of AI Systems, is Chair of the Society for Computers and Law, and is a non-exec director on the Board of iTechlaw and on the Board of Women Leading in AI. Until 2021, Patricia was on the RSA’s online harms advisory panel, whose work contributed to the UK’s Online Safety Bill.
Trish is also a linguist and speaks fluently English, French, and German.
In 2021, Patricia was listed on the 100 Brilliant Women in AI Ethics™ and named on Computer Weekly’s longlist as one of the Most Influential Women in UK Technology in 2021.
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