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Moxie Marlinspike, the privacy advocate who created the secure communication app Signal and its widely used open source encryption protocol, said this week that his privacy-focused AI platform, Confer, will start incorporating its technology into Meta\u2019s AI systems.<\/p>\n
Every day, billions of chat messages sent through Signal, Meta\u2019s WhatsApp, and Apple\u2019s Messages are protected by end-to-end encryption. The feature, which makes it impossible for tech companies and anyone other than the sender and recipient to snoop on your messages, has become mainstream over the past decade. As generative AI platforms explode in popularity, though, people are now also exchanging billions of messages a day with AI chatbots that don\u2019t offer the protection of end-to-end encryption\u2014making it easy for AI firms to access what you talk about.<\/p>\n
This is by design, given that platforms often want to train their AI models on as much user data as possible and have made it hard to opt out of having your information used as training data. But as chatbots and AI agents have become more capable, some technologists and companies are pushing to create more constrained and privacy-focused systems.<\/p>\n
\u201cAs LLMs continue to be able to do more, we should expect even more data to flow into them,\u201d Marlinspike wrote in a short blog post about his collaboration with Meta published on Tuesday. \u201cRight now, none of that data is private. It is shared with AI companies, their employees, hackers, subpoenas, and governments. As is always the case with unencrypted data, it will inevitably end up in the wrong hands.\u201d<\/p>\n
Marlinspike wrote that he will \u201cwork to integrate Confer\u2019s privacy technology so that it underpins Meta AI.\u201d He also emphasized that Confer, which debuted at the beginning of this year, will continue to operate independent of Meta. The project\u2019s goal, Marlinspike added, is to offer a technology that \u201callows everyone to get the full power of AI along with the full privacy of an encrypted conversation.\u201d<\/p>\n
In 2016, Marlinspike worked with WhatsApp, which is owned by Meta, to roll out end-to-end encryption to more than a billion accounts simultaneously. Over the last year, WhatsApp has introduced a Meta AI chatbot into its app, which isn\u2019t shielded from the company in the same way individual chats are.<\/p>\n
\u201cPeople use AI in ways that are deeply personal and require access to confidential information,\u201d WhatsApp head Will Cathcart wrote on Wednesday on the social media platform X about the collaboration with Confer. \u201cIt's important that we build that technology in a way that gives people the power to do that privately.\u201d<\/p>\n
The adoption of encrypted AI is still emerging. The cryptographic schemes used in end-to-end encryption for traditional digital communication aren\u2019t easily or directly translatable into data protections for generative AI. For its part, Confer is still a new project, and Marlinspike\u2019s blog post did not provide specific details about how exactly the collaboration with Meta will work or what the specific goals are for integration.<\/p>\n
Neither Marlinspike nor Meta provided WIRED with additional comment ahead of publication.<\/p>\n
Mallory Knodel, a cryptography researcher at New York University, says it would be \u201cgreat for people using chatbots that use Meta AI to have confidentiality and privacy within that exchange.\u201d Crucially, that means Meta would not be able to access AI chat data for training, says Knodel, who along with colleagues recently published a study on end-to-end encryption and AI. \u201cI really hope more AI chatbots adopt this approach.\u201d<\/p>\n
Knodel\u2019s preliminary, initial assessments of Confer indicate that the platform isn\u2019t perfect, but is an important example of how to build a private AI chatbot.<\/p>\n
Cryptographer JP Aumasson, the chief security officer at the cryptocurrency platform Taurus, has come to similar conclusions about Confer thus far. \u201cConfer is probably the best private AI solution, all things considered,\u201d he tells WIRED. \u201cIt's not perfect, of course. It lacks documentation of its architecture, threat model, and supply chain. But Moxie knows what he's doing and has a solid track record.\u201d<\/p>\n
The complexity of developing encryption schemes for AI platforms is a major hurdle, and much of the privacy work so far has focused on accessible open source models or building privacy layers between AI companies and end users. For example, as Marlinspike wrote on Tuesday, \u201cConfer\u2019s technology has been built on top of open weight models. While many people love using Confer for a wide variety of tasks, others have missed the frontier capabilities from proprietary models.\u201d<\/p>\n
The collaboration with Meta gives Marlinspike an opportunity to work directly with closed models. \u201cMeta is building advanced frontier models, so this will combine the most private AI chat technology in the world with the most capable AI models in the world,\u201d he wrote.<\/p>\n
Regardless of whether the project will ultimately fulfill all of those superlatives, researchers emphasized to WIRED that the collaboration is significant.<\/p>\n
\u201cMoxie's proposal of using trusted computing, a concept dating back at least to the 1990s, is sound to me,\u201d Taurus\u2019 Aumasson says. \u201cThe underlying assumptions and limitations are well understood. Again, it's not perfect, but probably sufficient for most users. The challenge is to support models that are as good as the latest frontier models from Anthropic and Google and OpenAI.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
Save StorySave this storySave StorySave this story Moxie Marlinspike, the privacy advocate who created the secure communication app Signal and its widely used open source encryption protocol, said this week that his privacy-focused AI platform, Confer, will start incorporating its technology into Meta\u2019s AI systems. Every day, billions of chat messages sent through Signal, Meta\u2019s […]<\/p>\n","protected":false},"author":1,"featured_media":47941,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[],"class_list":{"0":"post-47940","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-business"},"_links":{"self":[{"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/posts\/47940","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/comments?post=47940"}],"version-history":[{"count":0,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/posts\/47940\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/media\/47941"}],"wp:attachment":[{"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/media?parent=47940"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/categories?post=47940"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/agooka.com\/news\/wp-json\/wp\/v2\/tags?post=47940"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}