Are Technologists Ready for the Data Commodity of Ambient Intelligence?
February 13, 2018
Beth Kindig
Lead Tech Analyst
Savvy consumers today are aware that marketers and corporate companies mine personal data from mobile phones and computers, sourced primarily from search engines, social media sites, emails, text messages, and GPS location information. The internet, a free virtual public space idealized in the nineties, has become colonized through a swath of promised conveniences. In the beginning, the lure of free, convenient services for data was enticing. The improvement in user experience when checking email in the cloud was great enough so as not to elicit questions as to how the emails were handled – such as when Google launched Gmail in 2004, adding a second signal to enrich the profile of search engine users through personally identifiable information. GPS tracking has also since become a powerful method of gathering information on an individual. E-commerce sites advertise by dropping cookies to track online behavior. Thermostats, in a promise to lower heating bills, track data on how people behave inside their homes. But the underpinnings of demand for data by marketers and big corporations remains obscure to most individuals. What is the value of this data and is the digital privacy of individuals a fair trade for the use of internet services and applications?
Ambient Intelligence: A Higher Level of AI Cognition
Many believe that technology’s dominance over privacy is inevitable. Today, humans in developed countries occupy a mixed digital and physical space, one that is largely driven by automatic collection, trading and analysis of information with little or no effort to protect the fundamental rights and liberties of those who use the technology. As the physical and digital worlds merge, digital privacy is no longer a right, but rather a commodity to be traded and sold – meanwhile, physical privacy continues to be protected.
Technology is simply moving faster than policy mechanisms, and this allows technologists to impose their own rules. Big data has fueled a sharp uptick in data mining and profiling with the intent to predict human behaviors and preferences. A White House report released in October 2016 notes that big data is actually the precursor to artificial intelligence and that the availability of big data from e-commerce, businesses, social media, and science have “…provided the raw material for dramatically improved machine learning approaches and algorithms.”
Once interoperability evolves for the many facets of the Internet of Things, along with a higher level of AI cognition, ambient intelligence will emerge. In a world of ambient intelligence, devices work seamlessly to carry on life activities using information and devices hidden in the network. The devices will grow smaller and become more integrated into the environment. Imagine an AI-powered assistant delivering products and services to you the instant they are required; whether it’s a ride when you leave the airport, replacing the groceries you’ve eaten earlier in the week, or ordering your drycleaning. The point for the bots and sensors will be to learn and know as much about your personal habits as possible to increase convenience.
Clearly, technologists have some responsibility that is absent from the current discussion on AI and ambient intelligence. The general population may not demonstrate substantial concern (or understanding) to change its behavior or modify its choices, but that doesn’t mean that these mechanisms should go unchecked. Higher order thinking makes the case that people (and society) need more control over personal information, including any machines placed to observe, construct or produce knowledge on an individual.
What is the Value of Privacy – and do Consumers care?
“Control over personal information is control over an aspect of the identity one projects to the world, and the right to privacy is the freedom from unreasonable constraints on the construction of one’s own identity.” –Philip Agre
Gartner predicts that by 2018, 50 percent of business ethics violations will occur because of the improper use of big data and analytics. At the same time, some companies have railed against this, taking steps to distinguish themselves under a banner of data ethics. Services such as Whatsapp and Signal have shunned data collection entirely by using end-to-end encryption. This decision has helped eliminate potential liability in handling sensitive, personal data, because it simply isn’t retained.
However, not every company can grow – let alone survive – without some level of data science. Big data is the fuel source even as the “engines” such as mobile, artificial intelligence and ambient intelligence become more sophisticated and subtle in their operations. In this case, data platforms are driving these decisions, and those that have a policy for privacy ethics will statistically deliver more value as marketers, startups and corporate companies alike need to connect with consumers without creeping them out.
These proactive decisions can help to sway the perspective of consumers, especially in a competitive space. According to a study by The University of Pennsylvania, more than half of Internet users are concerned about protecting privacy, but feel it may be too late. According to Pew, 74% of Americans say it is “very important” to be in control of their personal information. Meanwhile, according to Chapman University, Americans’ number-one fear is of man-made disasters (e.g., terrorist attacks). A close second is the tracking of personal data by government and corporations, outranking concerns about crime, the environment and natural disasters.
At this point, to say that consumers “do not care about privacy” is to dodge the ethical responsibility that comes with collecting data. As technology advances to include our immediate surroundings, the discussion around big data deepens as it may affect identity and lessen autonomy. In the future, those who handle data as an intermediary– which means delivering the necessary data to first-party companies while buffering and protecting the information collected on consumers – will fare better professionally than those who approach sensitive information like a commodity.
More To Explore
Newsletter
Is the AI Dip a Buy? Key S&P 500 Levels and the One Bond Market Line to Watch
In our last broad market report on June 18th, we presented a case for caution, presenting numerous warning signs that we tend to see before a correction, ranging from institutional positioning to nume
Big Tech’s AI Revenue Is Surging, but Suppliers Will Still Be the Bigger Winners
Big Tech’s AI Capex has stomped estimates for multiple years and analysts are now calling for capex to surge to $1 trillion in 2027. However, hyperscalers have long battled investor concerns around wh
AI Capex to Hit $1 Trillion – And Estimates Are Still Too Low
Big Tech capex is the driving force behind the AI infrastructure trade, yet Wall Street has repeatedly underestimated the sheer scale of the buildout. Currently, in 2026, the guidance for $732.5 billi
Token Growth is Surging - Here Are the Beneficiaries
The reality of AI demand growth has shattered early estimates for token processing, yet expectations continue moving up and to the right. In the second installment of our token processing series, we e
AI Token Demand is Shattering Forecasts
Total annual token processing is no longer measured in billions or trillions of tokens, but in the quadrillions and beyond. As annual token processing is now tracked in units with 15 trailing zeros, i
Nvidia and Google Are Crowding TSMC’s N3 Node - Can Intel Fill the Gap?
Nvidia is moving its next-generation Rubin GPUs from 4nm to 3nm, yet Google’s latest TPUs are already on N3 and are expected to remain there. Meanwhile, a growing number of AI CPUs from Nvidia, Amazon
Intel vs TSMC: How CoWoS Packaging Constraints Could Create an Opportunity for Intel Foundry
Taiwan Semiconductor (TSMC) is the single, most important company to the AI industry. However, to compete with the incumbent, Intel does not need to beat TSMC at leading-edge manufacturing. It only ne
Big Tech’s Free Cash Flow is Turning Negative – Who's Next?
Big Tech’s AI revenue is accelerating, but free cash flow is moving sharply in the opposite direction. Across Google, Microsoft, Meta and Amazon, capex is rising much faster than operating cash flow a
Big Tech Earnings Preview: Is AI Monetization Finally Catching Up to Capex?
The most pronounced difference between 2026’s tech rally compared to rallies in the past is which companies have been left out of it. The names most associated with the AI trade have hardly participat
Nvidia, CXL, and the Battle to Improve AI Inference Economics
This is Part 2 of our two-part series on AI inference economics. In Part 1 — Why Nvidia's Next AI Battle Is About Tokens per Watt, we laid out why tokens per watt has become the defining metric for in
