Internet of bodies or IoB is a term that I first heard as The Internet of Bodies – a RAND Corporation report into internet connected devices that
…monitor the human body and transmit the data collected via the internet. This development, which some have called the Internet of Bodies (IoB), includes an expanding array of devices that combine software, hardware, and communication capabilities to track personal health data, provide vital medical treatment, or enhance bodily comfort, function, health, or well-being.
RAND Corporation were interested in the internet of bodies because of the complexity of the area. There are benefits which are well documented by others. However there are also ethical considerations around:
Data use by commercial organisations (advertising, health insurance, pharmaceutical industry)
Misleading product claims around product efficacy
Data security risks
Underdeveloped and complex regulatory environment
What the Internet of Bodies covers includes:
Fitness software running on smartwatches or smartphones and device sensors
Connected health devices: insulin pumps, pacemakers
Patient adherence apps on smartphones
Patient diaries about their condition
The report came to a number of conclusions including:
As 5G, Wi-Fi 6, and satellite internet standards are rolled out, the US government conduct research projects to better understand any potential issues that might emerge There is a challenge that needs to be addressed to replace earlier generation devices and services with poor information security practices. The issue of cybersecurity needs to have more attention paid to it, right from the beginning of IoB product development
Device makers should test products and services for vulnerabilities often, and devise methods for users to patch software.
Data transparency and protection regulations need to be revisited to take account of materials received from the IoB
As with any new sector, a tighter regulation is required to prevent false or misleading product claims
I came across the idea of CPO in GQ magazine. I know few people that have bought anything other than the G-Shocks in their collection for retail.
There’s a few reasons for that:
The watches that people like are often vintage models, it’s reverse of the hot streetwear and luxury ‘drop’ scene
With the exception of sought after models from the likes of Rolex; most watches suffer from a similar depreciation curve to buying a new car
If you’re buying a watch to wear, so I care less about the box, immaculate cardboard outer box and papers
A quality watch is a classic example of heirloom design. Whilst they will need to be serviced every three to five years; they can also last beyond the lifetime of the owner to be handed down in families.
A number of watch dealers that were known by word-of-mouth have gone to the wall. For instance, Austin Kaye, which had been a regular fixture on The Strand longer than I have lived in London closed at the end of 2019.
Online watch resellers have taken off. Crown & Caliber and WatchBox in the US; Watchmaster in Germany and Watchfinder & Co. from the UK – are some of the biggest players. Scale, brand trust and a panel of expert watchmakers have formalised the purchase process with validation that you’re not buying a fake or a ‘frankenwatch’.
This verification is usually called certified pre-owned or CPO in the trade. At first you used to see this in the Japanese luxury resale market provided by the likes of BRAND OFF.
BRAND OFF is trusted by luxury shoppers across East Asia.
It then extended to this new breed of online resellers. Luxury watch brands have bought some of the watch resellers. For instance, Richemont bought Watchfinder & Co. Other watchmakers, now have a formal process to CPO their watches.
Previously, you would have to submit a watch in for a service to get proof that the watch was legitimate. Some brands are even reselling CPO watches including H Moser & Cie. Pre-owned items offer the luxury industry an opportunity to be more sustainable. Greater involvement in the pre-owned market also allows watch brands to get more value from their products over time.
I first heard of the merge from Sam Altman’s blog. He said that it was a popular topic of conversation in Silicon Valley to guess when (not if) humans and machines will merge. In a meaningful way rather than just a Johnny Mnemonic-style walking data storage unit.
When I heard of this definition of the merge, I immediately thought of the digital series H+.
H+ told the tale of a technological hack that killed people by disrupting the implants in their heads. Some of the few survivors were out of cellular network reach in the basement of multi-story car park.
He went on to explain that it may not be a hybridisation of humans literally with technology but when humans are surpassed by a rapidly improving (general purpose) AI. The third possibility was a genetically enhanced species surpassing humans in the same way that homo sapiens surpassed the neanderthal.
What’s interesting is that some of the people don’t give ‘the merge’ a name at all. Back during the dot com boom, when Ray Kurzweil published his book Age of Spiritual Machines it was given the name The Singularity.
Part of the resistance to this established term was that The Singularity implies a single point in time. I don’t think Kurzweil meant it in that way. But its been almost 20 years since I read Age of Spiritual Machines, and I suspect most of the debaters have only read about it from a Wikipedia article.
Alton points out that in some ways the merge has been with us for a good while.
The contacts app on our devices and social networks take the place of us remembering telephone numbers. I can remember my parents landline number and the number of the first family doctor that we had. But I wouldn’t be able to tell you my parents current cell phone number; or the number of my current doctor.
On a grander scale; general knowledge and desire to read around has been depreciated by Google and Wikipedia. Our phones, tablets and laptops are not implanted in us, but at least one of them will be seldom out of reach. I learned to touch type and I am now not conscious of how I input the text into this post. It goes from my thought to the screen. Only the noise of the keys gives away illusion of mind control as I stare at the screen. Ironically voice assistance makes me more conscious of ‘the other’ nature of the device.
But it no longer just about memory and our personal connectedness of the devices. Our device control us and suggest what to do and when. Social media platform curation affects how we feel.
As Altman puts it:
We are already in the phase of co-evolution — the AIs affect, effect, and infect us, and then we improve the AI. We build more computing power and run the AI on it, and it figures out how to build even better chips.
This probably cannot be stopped. As we have learned, scientific advancement eventually happens if the laws of physics do not prevent it.
Innovation often spits out the same process in several waves before it works. Before Siri, Alexa and Google home there was Wildfire. Before Wildfire there were various speech recognition technologies including Nuance for call centres, Lernout & Hauspie, Dragon Systems and Kurzweil Computer Systems. The last two were founded in the mid-1970s. SRI International’s AI research started delivering results in the mid 1960s.
AI in its broadest terms has gone through several research booms and busts. The busts have their own name ‘AI winters’. The cadence of progress could easily be far slower than Altman imagines.
One could easily argue that machine learning might run its natural course to technical maturity without much more improvement. Google and other technology companies are basing their work on research done at Canadian universities in the 1980s during an ‘AI winter’ characterised by a lack of basic research funding. Canada continued to support the research when others didn’t.
Silicon Valley companies not engaging in basic research themselves. As Judy Estrin observed in her book Closing The Innovation Gap back in 2008, Silicon Valley no longer engages in ‘hard innovation’. Without that basic research; a general purpose AI envisioned by Kurzweil and Altman maybe out of reach. Which is why Silicon Valley pundits put the merge as somewhere in a 50-year window.
Altman also caveats his prediction based on the laws of physics. Aaron Toponce : The Physics of Brute Force provides an idea of the physical limits imposed by cracking cryptography. It would not be inconceivable that a general purpose AI may hit similar challenges. More on machine learning and innovation here.