Just a sample of the Echomail archive
Cooperative anarchy at its finest, still active today. Darkrealms is the Zone 1 Hub.
|    CONSPRCY    |    How big is your tinfoil hat?    |    2,445 messages    |
[   << oldest   |   < older   |   list   |   newer >   |   newest >>   ]
|    Message 2,360 of 2,445    |
|    Mike Powell to All    |
|    When machines remember us    |
|    10 Feb 26 17:16:36    |
      TZUTC: -0500       MSGID: 2118.consprcy@1:2320/105 2df0ec8a       PID: Synchronet 3.21a-Linux master/123f2d28a Jul 12 2025 GCC 12.2.0       TID: SBBSecho 3.28-Linux master/123f2d28a Jul 12 2025 GCC 12.2.0       BBSID: CAPCITY2       CHRS: ASCII 1       FORMAT: flowed       When machines remember us: Rethinking privacy in the age of humanoids              Opinion By Dr. Najwa Aaraj published 8 hours ago              How humanoid AI will redefine privacy, trust, and dignity              As policymakers race to regulate AI, a more intimate form of artificial       intelligence is emerging quietly, yet profoundly. The next revolution in       technology will not arrive as an app or an algorithm. It will walk toward us,       look us in the eye, and ask how it can help.              Humanoid robots are poised to leave the laboratory and step into our daily       lives: greeting guests in hotels, assisting patients in hospitals, tutoring       children, guiding us in malls, and eventually sharing our workplaces and homes.              Goldman Sachs forecasts that consumer sales will surpass one million units by       2035, a signal that this future is not speculative, but rapidly approaching. As       their forms become familiar, their presence will test one of humanity's       oldest instincts: the desire for privacy.              New era of trust              Until now, our digital existence has unfolded through screens and sensors we       could switch off. A phone slips into a pocket; a smart speaker rests quietly on       a shelf. But a humanoid is different. It observes, learns, reasons and acts       continuously.              It can read tone, posture, and emotion, capturing data far beyond what a       microphone or camera could record. In the age of humanoids, privacy will no       longer mean simply protecting what we say. It will mean defining what machines       are allowed to know about who we are.              This shift demands a new kind of trust. For decades, technology companies have       asked for our "consent" through lengthy forms and hidden clauses. Yet no       checkbox can capture the complexity of interacting with a learning, adaptive       robot.              When a humanoid helps an elderly patient stand, it must analyze posture,       predict balance, and detect hesitation. Every gesture produces intimate data.       But who owns those fleeting moments; the patient, the hospital, or the       robot's creator? And how can we ensure such data serves human dignity rather       than convenience alone?              Privacy preserving technologies              Existing privacy laws were built for files, not faces, for static storage, not       dynamic interaction. With humanoids, privacy becomes fluid, negotiated in real       time through movement, proximity and context.              Policymakers will need adaptive regulatory frameworks that evolve as quickly as       these systems do, incorporating continuous risk assessments and ethical design       principles from the very start. This is privacy by architecture, engineering       discretion so that it is not optional, but automatic.              At the core of this architecture lie cryptography and cryptographic protocols,       the science that makes privacy enforceable by design.              They enable humanoids to learn and respond to human needs without revealing the       underlying data. Rather than trusting that sensitive information won't be       misused, cryptographic techniques ensure it cannot be accessed in the first       place. This is the difference between policy promises and mathematical       guarantees.              In a world where humanoids continuously observe, interpret, and act, such       guarantees are essential. Encryption and privacy-preserving technologies can       transform ethical intentions into operational safeguards, anchoring trust in       the code itself.              Modern privacy engineering already offers tools for this vision. Techniques       such as federated learning, homomorphic encryption, and secure multi-party       computation allow AI systems to learn from local data without exposing it.              A humanoid can thus improve its assistance over time while keeping sensitive       information within its own encrypted domain. Privacy, in this sense, is not       just a social value, it is a scientific discipline advancing in parallel with       robotics.              Yet, the code behind humanoids must reflect more than just technical function,       it must embody social norms. In many cultures, cues like posture, gaze, and       proximity signal respect or intrusion.              Robots that move among us must be attuned not only to our privacy but to our       customs, boundaries, and emotional comfort. Trust will depend not just on what       machines can do, but on how gracefully and respectfully they do it.              If we embed privacy and dignity at the heart of humanoid systems, through both       code and conduct, these machines can help us reclaim control over data that       today flows unchecked through digital platforms.              A care humanoid can allow elderly individuals to live independently without       constant human oversight. A humanoid tutor can keep a child's learning data       safer than a cloud-based platform by processing it locally. The goal is not to       reject these technologies, but to guide them toward humane, transparent, and       ethical ends.              Respect, discretion and care              As a scientist and researcher, I see robotics as a mirror, reflecting not only       our engineering ambition but our ethical imagination. At the Technology       Innovation Institute, we are building physical artificial intelligence that       must engage with the world in all its complexity.              This means designing not only for function, but for respect, discretion, and       care. As we teach machines to perceive us, we are also redefining - with       intention - what it means to be truly seen.              The task before policymakers, scientists, and citizens is to move from reaction       to anticipation, to write the rules of coexistence before machines arrive at       our doorsteps. Privacy, once a personal concern, must now become a shared       design principle.              Humanoids are arriving at a defining moment for society. Their emergence will       test our ability to govern technology with foresight, ethics, and compassion.              If we succeed, we will build a future where physical artificial intelligence       safeguards, rather than sacrifices, human potential; proving that innovation       and integrity can coexist by design.                     This article was produced as part of TechRadarPro's Expert Insights channel       where we feature the best and brightest minds in the technology industry today.       The views expressed here are those of the author and are not necessarily those       of TechRadarPro or Future plc. If you are interested in contributing find out       more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro                     https://www.techradar.com/pro/when-machines-remember-us-rethinking-privacy-in-t       he-age-of-humanoids              $$       --- SBBSecho 3.28-Linux        * Origin: Capitol City Online (1:2320/105)       SEEN-BY: 105/81 106/201 128/187 129/14 305 153/7715 154/110 218/700       SEEN-BY: 226/30 227/114 229/110 134 206 300 307 317 400 426 428 470       SEEN-BY: 229/664 700 705 266/512 291/111 320/219 322/757 342/200 396/45       SEEN-BY: 460/58 633/280 712/848 902/26 2320/0 105 304 3634/12 5075/35       PATH: 2320/105 229/426           |
[   << oldest   |   < older   |   list   |   newer >   |   newest >>   ]
(c) 1994, bbs@darkrealms.ca