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Will the U.S. ever regain its lead in privacy protection?

Privacy matters. A quick thought experiment about online and offline privacy shows us why. Let’s say you own a grocery store. And at that store, you have a security camera positioned to record everyone who walks through your door. Customers entering the store understand that the camera is going to record their images and activities while they’re in the store. If a particular customer thinks about this agreement at all, it’s most likely to find it a reasonable exchange of privacy. 

With a digital service like a social media app, this privacy exchange is markedly different. Because when an individual installs and uses an app, they are required to agree to what amounts to digital surveillance. The app provider gets to know everything about what users do inside the app; and in many cases actions they take outside of the app. Each user “agreed” to this surveillance via the app maker’s Terms and Conditions and Privacy Policy when they signed up for the service, but often did so by default rather than expressly affirming consent. And since all of the surveillance happens invisibly, the consumer is able to conveniently ignore the data collection and everything that happens to the data after it’s collected. 

Now back to the grocery store. For the store to match the same level of surveillance as the social media app we described, its security camera would need to capture not just faces, but names, addresses, birthdays, heights, weights, dietary habits, brand preferences, favorite meals, frequency of cooking at home, conversations about food with friends, and so on. And if simply walking into the store touched off that level of surveillance, a lot of us would be hesitant to walk into the store. Yet billions of people around the world make daily use of digital products that do just that.

The reason that 91% of Americans agree they have lost control of their personal information is because they have. The corporations providing our favorite digital services hold all of the privacy cards. So it’s interesting that in Europe, things are different. One survey found that 31% of respondents felt they had “no control at all” over how their data was used. Why the difference? To understand the state of privacy law in America today, you need to go back to the 1970’s and 1980’s. 

At the dawn of the digital age the U.S. established an early lead in enumerating principles and passing laws designed to protect individual data privacy. Those principles would inspire other countries, and the EU in particular, to enact increasingly pro-consumer privacy laws, culminating in the EU’s expansive 2016 General Data Protection Regulation (GDPR). GDPR is a unified privacy standard applicable to any company or group collecting and handling personal data about EU citizens. 

All is not lost for U.S. privacy policy. Steps could be taken to improve privacy protection and put the U.S. back on the path to leadership in privacy law. But first, the history.

Privacy law at the birth of computing

The U.S. is often criticized by her European counterparts for not having implemented robust and universal data privacy laws. 

Yet most people don’t realize that the privacy laws

operating in many countries today are built on foundational principles that emerged from the Fair Information Privacy Practices (FIPPs) framework developed in the U.S. in the 1970’s. 

FIPPs defined core digital privacy principles like:

• Notice. A consumer must be told that data has been collected and how it might be used.

• Choice. Defining how data can be used, including the right to opt-in or opt-out.

• Access. A consumer’s right to see data about themselves and verify or contest its accuracy.

FIPPs emerged in the 1973 U.S. Advisory Committee Report on Automated Data Systems. The report was prepared by the Secretary of Health, Education, and Welfare in response to the first major computer systems containing what today we would call personally identifiable data. The Forward to the report begins with a surprisingly prescient pronouncement: “Computers linked together through high-speed telecommunications networks are destined to become the principal medium for making, storing, and using records about people.”

The report goes on to propose fundamental principles for designing and regulating computer systems that record, store, and protect data about one or more aspects of the life of a specific person. This was a major milestone for digital privacy. The language in the report remains highly relevant today: 

“An individual’s personal privacy is directly affected by the kind of disclosure and use made of identifiable information about him in a record. A record containing information about an individual in identifiable form must, therefore, be governed by procedures that afford the individual a right to participate in deciding what the content of the record will be, and what disclosure and use will be made of the identifiable information in it. Any recording, disclosure, and use of identifiable personal information not governed by such procedures must be proscribed as an unfair information practice unless such recording, disclosure or use is specifically authorized by law.” 

In plain language, this passage translates into something like: “If I say you can make a record about me, you agree that I’ll know exactly what is recorded and how it will be used; and I’ll have the right to correct or delete it if it’s wrong. Any behavior outside of these limits is illegal.” This was FIPPs in a nutshell.

In the 1980’s, FIPPs went international. The Organization for Economic Co-operation and Development (OECD) embedded FIPPs in its privacy guidelines. The OECD is an intergovernmental economic organization with 35 member countries, including most of the world’s largest economies. The OECD published data privacy guidelines to which its members agreed to voluntarily adhere. Again, the language of this agreement seems fresh and relevant today. The OECD guidelines recognized:

“That, although national laws and policies may differ, Member countries have a common interest in protecting privacy and individual liberties, and in reconciling fundamental but competing values such as privacy and the free flow of information.”

It was already clear that a natural tension existed between an individual’s right to privacy and a corporation’s desire to profit from that individual giving up some of that privacy.

Back in Europe, FIPPs was at the heart of the Council of Europe’s “Convention 108” treaty in 1981. The Council of Europe is the continent’s leading human rights organization. Its membership is larger than the more exclusive EU, and its primary purpose is promoting human rights. Emphasis on “rights.” Because here we see FIPPs graduate from what had been principles in the U.S. to what became a right in Europe. Again, the language is relevant today: 

“This Convention is the first binding international instrument which protects the individual against abuses which may accompany the collection and processing of personal data and which seeks to regulate at the same time the transfrontier flow of personal data. In addition to providing guarantees in relation to the collection and processing of personal data, it outlaws the processing of ‘sensitive’ data on a person’s race, politics, health, religion, sexual life, criminal record, etc., in the absence of proper legal safeguards. The Convention also enshrines the individual’s right to know that information is stored on him or her and, if necessary, to have it corrected.” 

On the path to the right to privacy

Since the Internet era began in the 1990’s, the U.S. has taken a back seat to the EU in the continuing development of privacy laws. 

By the mid-1990’s, the EU sought to address inconsistent enforcement of the Convention 108 treaty by passing the EU Data Protection Directive in 1995. This was a major step toward achieving EU-wide uniformity in every sector of society. Here we see clearly that privacy is firmly enshrined as a right. Article 1 of the law defined the importance of individual privacy succinctly: “Member States shall protect the fundamental rights and freedoms of natural persons, and in particular their right to privacy with respect to the processing of personal data.” 

To understand just how differently privacy was treated in the EU and the U.S. at this time, we need only ask what was happening in the U.S. in 1995. Rather than attempt a comprehensive privacy approach, the U.S. was creating narrow, sector-specific privacy laws covering, for example, our health records, our children, our driving records, and our financial records. We recognized that certain parts of our lives deserved special privacy protection mandated by the government but we stopped short of applying the same principles to other parts of our lives. And, importantly, we left the rest of our privately identifiable information as fair game. But why?

It’s an important question, and one the EU answered with the General Data Protection Regulation, the granddaddy of consumer-friendly privacy laws. The European Commission approved GDPR in April 2016 and it is expected to be enacted by May 2018. GDPR is Europe’s attempt to harmonize data protection regulations and even attempts to extend EU privacy principles to any company doing business with EU citizens.

FIPPs, and the U.S.’ lead in digital privacy law, is today a footnote to a footnote.

What the U.S. can do to protect its citizens

Today, more than 100 data protection laws exist worldwide. And all of those laws have a common set of core principles which consist of: notice to consumers; transparency towards individuals regarding how their information will be used; choice for the individual, furnishing them the opportunity to give consent or to object to how their data is being used; access to their data, for example, to correct the information should it be out of date; and security of their data. 

The problem isn’t that the U.S. lacks any privacy regulation. In fact, there are laws like the Fair Credit Reporting Act of 1970 (FCRA), the Driver’s Privacy Protection Act of 1994 (DPPA), the Health Insurance Portability and Accountability Act of 1996 (HIPAA), and the Children’s Online Privacy Protection Act of 1998 (COPPA). And, in addition, most states have enacted some form of privacy legislation. The problem is that U.S. laws only provide some protection for some of our personal identifiable information, not comprehensive protection for all of our data.

But there are two significant omissions in privacy protection in the U.S. today: universal protection for the core privacy principles once enshrined in FIPPs; and the fundamental recognition to a right to privacy. To regain its leadership in privacy rights, the U.S. could: 

1. Expand privacy as a right for all personal identifiable information, not just for some. 

2. Ensure that before any data collection, consumers are clearly and simply informed of exactly what personal data will be collected prior to opting in.

3. Prohibit data collectors from selling personal data collected without express permission of the consumer.

In today’s global business environment, GDPR’s relevance to companies doing business in Europe means that practically every U.S. multinational will be required to abide by that law. Formal adoption of a universal, comprehensive, consumer-friendly privacy law could benefit American consumers and businesses alike. There is still much history to be written.

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Ah, the fresh smell of smartphone in the morning!

What’s the first thing you think of in the morning? According to one survey about trends in consumer mobility, 35% of us think about our smartphones, 17% of coffee, 13% of a toothbrush, 10% of a significant other, 6% of a remote control, and 4% of a bathrobe. There were interesting findings in a different mobile consumer survey: 50% of us check our mobile devices in the middle of the night, and more than 1 in 3 check devices right before bed. Which is easy to do because 71% of us are sleeping with—or next to—their mobile phones.

With a lot of data like this, the findings are neither “good” nor “bad.” That’s too simple. Instead, they give us fascinating insights into how rapidly our trusty mobile devices have become central to how we interact with the world around us. At Entefy, we like the positive sides of these changes—the countless opportunities for person-to-person connection that exist today. It’s not all perfect, but it’s certainly inspiring. 
Entefy’s enFacts are illuminating nuggets of information about the intersection of communications, artificial intelligence, security and cyber privacy, and the Internet of Things. Have an idea for an enFact? We would love to hear from you.

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Cars collect data about you too

The amount of data self-driving cars generate is staggering. One industry insider estimates that 1 million self-driving cars will generate as much data as 3 billion people. Last year in the U.S. alone, one major car company collected 4,220 terabytes of data from customers’ cars. To put that into perspective, 99% of Comcast users don’t use up the one terabyte allotted to them each month

Data collection by self-driving cars is a growing market. Why do car companies collect data? Some data provides insight into how the car is running. The rest reveals what people are doing and where they’re going, information that’s sought after by retailers, marketers, governmental organizations, and more. McKinsey forecasts that this type of data collection could become a $450 to $750 billion market by 2030.

As things stand today—whether you’re browsing online, walking past a store front, even driving a car—it’s hard to get around the fact that everything we do generates data, and that data finds its way into growing resale markets.  

Entefy’s enFacts are illuminating nuggets of information about the intersection of communications, artificial intelligence, security and cyber privacy, and the Internet of Things. Have an idea for an enFact? We would love to hear from you.

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Oops, I forgot [VIDEO]

You memorize and memorize and memorize some more, trying to get something new to stick. And then whoops! You forget most of it a short time later. Sound familiar? Don’t worry, you’re not the only one. Because research confirms that there’s a universal rate of forgetting. A 19th century psychologist was able to map the rate of decline in memory retention after learning new information. 

This video enFact explains how the Ebbinghaus forgetting curve works. If you’ve ever gotten frustrated not being able to fully remember a book, movie, or test notes…rest easy. It’s just the way our brains work. 

Read the original version of this enFact here.

Entefy’s enFacts are illuminating nuggets of information about the intersection of communications, artificial intelligence, security and cyber privacy, and the Internet of Things. Have an idea for an enFact? We would love to hear from you.

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Patients are about to see a new doctor: artificial intelligence [SLIDES]

The health care industry has already seen advanced artificial intelligent systems make an impact in areas like medical diagnosis and patient care. But the long-term big-picture importance of AI in medicine may be something else entirely: a potential fix for the intractable problem of too few doctors and nurses worldwide. And as part of that, a solution to health care’s public enemy number one—paperwork. 

Entefy curated a presentation based on our article “Patients are about to see a new doctor: artificial intelligence.” These slides provide a snapshot of how AI is at use in medical care today, the advances and limits of current AI systems, and AI’s potential in patient care. The presentation contains useful data and analysis for anyone interested in the intersection of AI and medical care. 

David and Goliath

The modern David and Goliath: AI-powered startups take on the Fortune 500

People love a good David and Goliath story. Thanks to artificial intelligence, we may once again see many iterations of this narrative play out in the business space. 

For a long time now, big corporations have held most of the cards. Their capital, brand recognition, large staffs, and access to data have dwarfed the resources and capabilities of small businesses. So much so that in 2015, the Global Fortune 500 represented $27.6 trillion in revenues and employed 67 million people. This is a stunning concentration of power in a relatively small number of corporations.

But AI is changing competitive dynamics and leveling the playing field in several ways. AI systems are becoming more advanced even as the cost to develop or access these systems is declining. We’re approaching a time when AI technologies will facilitate smarter, faster business processes at lower costs, allowing for some serious disruptions of existing markets by newcomers. It’s becoming possible to imagine a five-person startup going head to head with a Fortune 500 behemoth. Here’s how it might work. 

Is history about to repeat itself? 

One of the most dramatic David and Goliath business stories of our time is that of Microsoft outmaneuvering IBM in the 1980s. At its peak market capitalization in 1985, IBM was larger than Apple is today, accounting for 6.4% of the market value of the S&P 500 (compared to Apple around 4% today). With scale, personnel, capital, and clout, IBM seemed untouchable. 

IBM was a pioneer in computing, but it was blinded by its own success. The company focused on mainframes and developed big, clunky computers as it always had. It invested heavily in large-scale enterprise computing even as advances in technology allowed for the advent of the personal computer market. 

That’s when Microsoft seized its chance. The story of Microsoft’s development and release of MS-DOS while working on an operating system for IBM is the stuff of Silicon Valley legend. Microsoft knew that personal computing was a market with huge potential. As a smaller, more agile company, it was better-positioned than IBM to capitalize on it. By focusing on graphical user interfaces (GUIs) that could be used in personal computing, Microsoft catered to an entirely new market for home computers and found a way to outcompete its industry-dominating client. 

Today’s big tech corporations should heed IBM’s disruption as AI becomes an increasingly significant component of their business operations. Many of the largest brands in the world are using AI to address their internal needs, building improved advertising systems, bolstering product recommendation algorithms, and collecting data for business intelligence (BI) systems. AI’s primary purpose in those cases is to serve the companies’ needs, not cater to their customers. 

Focusing on internal needs and legacy systems—IBM’s strategic mistake—leaves the door open to the same technologies being applied to new products and customer experiences by disruptive competitors. Small businesses don’t need to spend heavily on operational improvements. They can direct their AI investments into consumer-facing products, targeting market segments that are overlooked or underserved by major corporations. 

Take one San-Francisco-based startup using AI to disrupt the lingerie industry. Knowing that most women find bra shopping a grueling experience, the company created an app that enables women to find the perfect fit from the comfort of their own homes. The app uses AI to analyze photos submitted by the women to determine their sizes, a much more comfortable experience than being sized in-store while other customers may be milling around nearby. The application of AI to a novel business offering neutralizes the advantages of large networks of stores and existing brands.  

In another example of disruption through AI, travel companies have begun using behavioral data and predictive analytics to customize brand experiences based on individuals’ preferences and patterns. Using this technology allows them to compete with major travel brands through unique, personalized offerings. That’s a powerful differentiator, considering that consumers crave personalization but delivering it can be a challenge. 

No personnel, no problem

One traditional advantage of entrenched enterprises is large teams of highly specialized workers. These companies can attract top-tier talent and have the resources to hire employees for whatever critical tasks arise. Small businesses, meanwhile, get by with team members who are often jacks-of-all-trades by necessity. 

But AI is neutralizing the large staff advantage, laying bare its associated limitations, like more bureaucracy and slower execution times. A smaller organization doesn’t suffer from those limitations because its teams can be flat and agile. Now add AI to the mix. AI-based services are capable of handling administrative tasks such as scheduling, invoicing, data entry, and even legal work. Right out of the gate, startup founders can outsource essential but low-level tasks to automated systems that operate faster and cheaper than human employees. Automating IT functions alone reduces expenses by 14% to 28%, so companies that launch using automated services quickly establish a financial advantage over larger, legacy burdened competitors.

For higher-level tasks, many AI software systems now include intuitive dashboards that anyone on the team can access and utilize productively. Centralized data hubs allow colleagues to draw from the same pool of information and track how their efforts impact the rest of the company.

Next generation customer-relationship management (CRM) systems, for instance, could be a game-changer for small businesses. CRMs help companies track important information about their customers—what they’ve purchased in the past, when they’ve interacted with the organization’s website, what they’re saying about the brand on social media. But CRM systems are generally cost-prohibitive for new businesses. They also only work if salespeople input customer data, and that’s a tedious, time-consuming task akin to analog paperwork.

That’s why some companies use AI assistants to integrate data from sales reps’ smartphones and work-related apps. Rather than spend hours inputting or scrolling through customer data, they’d have all the information they need at their fingertips. Without having to focus on low-level tasks like data entry, sales representatives can focus on building long-term customer relationships that lead to increased earnings for their companies. 

Real-time campaign analytics systems enable small, nimble organizations to pivot quickly based on performance. That ability is a critical competitive edge in today’s rapidly evolving consumer markets. Some tech experts believe that the current generation of applied AI systems, such as predictive analytics, will give small businesses advantages through increased automation and efficiency.  

Cloud services and automated marketing programs also reduce costs and personnel needs considerably. The barrier to launching and growing a company successfully has lowered significantly, and the rise of adaptive small companies is closing the gap between the little guys and the titans of industry. 

An example of this is in fintech, where startups are taking on major investment companies. They’re using dashboards and roboadvisers to offer smarter, more user-friendly ways for consumers to track, manage, and plan their investments. They expect AI to disrupt financial advisory services, and they’re building that anticipation into their services. Such foresight makes them uniquely suited to meet shifting consumer demands even when legacy organizations may struggle to keep up.  

Attacking the large company data advantage

One area in which Fortune 500s may still hold an advantage is in their vast stores of customer and market data. That information can be used to make predictions and inform product development, and newer, smaller companies simply don’t have the same data pool from which to draw. 

However, massive amounts of open source intelligence (publicly available data) on consumers is generated every day. People’s online behaviors, social media activity, and even geolocation check-ins contribute to a growing data pool that small businesses can tap.   

As increasingly sophisticated data tools become available to small enterprises, they may be able to close the data gap further. Business intelligence software was once so costly and complex, only major companies could afford to buy it and hire IT personnel who could make sense of it. Today, smaller businesses are taking advantage of the growing range of lower-cost BI solutions that essentially work out of the box. There’s no need to hire a team specifically to work with the software; it’s intuitive enough that anyone can draw insights from it. 

New BI platforms offer data visualization, customer relationship management programs, and other critical BI services. One micro-lending company uses a modern BI program to conduct performance analyses of its beneficiaries. It can now identify under-performers in a fraction of the time it took when relying on spreadsheets. This is just one way BI is enabling businesses of all sizes to make faster, smarter decisions. 

Focus on customers and their needs

Increasingly tech-savvy consumers demand seamless, automated user experiences, and a new generation of innovators will rush to meet the demand. AI is enabling these companies to compete based on the quality of their products and move quickly into new markets free of any legacy technology burden—basically, to apply the early Microsoft vs. IBM formula to today’s business environment. With the increasing automation and analytical benefits of AI systems, these companies can use the technology to assist with report writing, improve job listings, data crunching, and a range of other functions. Fewer people can do more with less.

As AI becomes more ubiquitous, small businesses will find further opportunities to go up against major players. The balance of power looks likely to shift from the biggest companies with the greatest resources to those that can quickly create innovative services that satisfy real needs for consumers. 

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“Text neck” is like carrying 5 gallons of paint on your head

We know that smartphone use is changing our behavior. But there is evidence that our handy digital companions are also changing our bodies. 

The healthiest posture is when you stand with your ears aligned with your shoulders and your shoulder blades retracted. But that’s not what we do when we, say, walk and text. We tilt our whole head forward to focus on the screen. Call it “text neck.”

According to one study into stresses of the cervical spine, this posture creates undue pressure on your spine. And the more you bend your neck, the worse it is for your spine. So much so that a relatively modest 15-degree tilt of the head creates the equivalent of 27 pounds of pressure on your spine. That weight increases the more you tilt: 40 pounds at 30 degrees, 49 pounds at 45 degrees, and a shocking 60 pounds at 60 degrees. Which is like carrying an 8-year-old child on your head. Or a punching bag. Or 5 gallons of paint. 

Incidentally, it is estimated that people spend on average 4.7 hours daily on their smartphones. This represents the potential for more than 1,700 hours a year spent stressing out your spine. Entefy’s enFacts are illuminating nuggets of information about the intersection of communications, artificial intelligence, security and cyber privacy, and the Internet of Things. Have an idea for an enFact? We would love to hear from you.

Every day is Earth Day

Entefy sends green wishes to everyone celebrating Earth Day this weekend. Since the first Earth Day in 1970, the event has grown to include 1 billion people in 195 countries

Environmental problems can seem so big compared to the scale of our day-to-day lives. Climate change. Biodiversity. Pollution. But it’s all a matter of perspective. Because when a lot of people act in concert, change can happen at the global scale. That is, after all, how Earth Day came about. 

So in that spirit, here are some specific actions you can take today to contribute to a healthier, greener Earth.

Waste is accumulating in the oceans. The World Economic Forum estimates that, pound for pound, there will be more plastic waste in the oceans than fish by 2050. Even more concerning, there’s no practical solution on the horizon. But we can reduce the rate this pollution accumulates with new behaviors. Stop purchasing single-use plastic drink containers. Refuse throwaway plasticware at restaurants. And, of course, recycle. Read about 7 ways to reduce ocean plastic pollution here.

Global temperatures are rising. The politics of climate change are controversial and wrapped in partisanship. But we can all agree that using less energy leads to slower depletion of natural resources. There are a lot of easy-to-do actions that will reduce your energy use. Use compact fluorescent lightbulbs. Car pool and use public transit. Lower your thermostat in winter. See this excellent list of 10 actions you can take today

Biodiversity is at risk. Life on Earth is defined by intricate connections between species. So reports that human activity has touched off a global extinction event are deeply troubling. With such a massive, global problem, what’s to be done? Again the logic holds that small changes in behavior can have outsized impact. Start with understanding how deforestation impacts habitats. And make biodiversity-friendly decisions when traveling and dining out.

It’s easy to get caught up in numbers when talking about the environment. But there’s only one number that really matters: 1. Because there’s only 1 Earth, we all need to treat her kindly. And we only get 1 shot at preserving a healthy, green environment for life in all its wondrous forms. 

Entefy’s enFacts are illuminating nuggets of information about the intersection of communications, artificial intelligence, security and cyber privacy, and the Internet of Things. Have an idea for an enFact? We would love to hear from you.

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Old school no more: AI disrupts the classroom [SLIDES]

Over the years, multiple digital technologies have been heralded as the next big thing in education—personal computers, apps, and, now, artificial intelligence. Will AI be different? It has the potential to reshape classrooms and transform education in the years ahead. 
While the first generation of “AI Ed” will likely be limited to systems that supplement teaching, it’s possible to imagine an AI-powered teacher replacement. And if we can imagine it, history shows that we’ll eventually create it. What do these developments mean for parents, students, and teachers?
Entefy curated a presentation based on our article about the impact of artificial intelligence in the classroom. These slides provide a look at education today, the promise and limits of current AI Ed offerings, and the possibilities of tomorrow’s AI-powered education. The presentation contains useful data for anyone interested in AI and education. 

Mom

Would you unfriend your Mom for the chance at a better loan?

Artificial intelligence is powered by algorithms and the effectiveness of those algorithms is in large part determined by the data they work with. So developments in the use of AI in consumer lending are of interest because lenders, particularly alternative finance platforms, have begun using the social media data of loan applicants to determine their creditworthiness

This trend carries the potential to create new consumer-friendly financial products but it also raises substantial concerns about privacy and bias. Issues that we’ll delve into here. We’ll start with a look at the ways our use of social media is changing, and then look at what those changes mean for social’s use in determining whether or not an applicant receives a loan.

The way we use social media has evolved 

Human beings are having a collective social media identity crisis. What began as a means of sharing our lives with friends and family has evolved into something more calculated and less, well, social. From a pastime to an obligation. 

In their early days, social media platforms offered people new ways to connect with their loved ones. We started carving time out of our day to check friends’ status updates or photos of a family member’s trip overseas. Social media gave people new options for connection and inspired closeness with people who were geographically far apart. 

But social media has evolved into something far more complicated. Our social shares began impacting our career prospects. Evidence emerged that online interactions were fraying real-life relationshipsCyberbullying became a real concern. Many people responded to these developments by carefully curating their social media presences. We learned to be more mindful of what our online activities revealed about ourselves, and weighed each post, comment, and opinion against how it would impact us offline. We became aware of a simple truth: the data we create will outlive us all.

More recently, we’ve started asking more sophisticated questions about social media use. Do we pay a price for constant connectivity? Not just in career opportunities but in interpersonal relationships as well. Is the experience of round-the-clock notifications detracting from the quality of our lives? Are we sacrificing precious time with friends, family, and romantic partners for diminishing returns on social media? 

Now with rapid advancements in artificial intelligence we have a new generation of considerations. Friends and employers aren’t the only ones evaluating our social activity. Ahead lies an era where the articles we post, photos we share, and even who we friend could impact our financial lives. 

Here’s how social media-powered lending would work

Proponents of the use of social media data in lending say that the use of social data will help, not harm, potential borrowers. Including people with poor or minimal credit histories. Let’s say you want to take out an auto loan but have a weak credit score and little collateral. Your application is rejected based on a traditional risk assessment, but then the lender offers you the chance for a ‘second look.’ If you allow them to analyze your social media profiles, they’ll use that information to do a deeper evaluation that may result in an approval.

This review might include verifying your location and educational background via social data, along with an analysis of your online connections. If you’re connected to people in high-paying jobs, for instance, an alternative underwriting system might determine that you’re on an upward financial trajectory and are therefore likely to repay your loans. 

In situations where social media use is voluntary and expands access to credit and other financial products, these new approaches have the potential to be groundbreaking. 

Borrowers face entirely new questions about personal privacy

The challenge right now is that you don’t know how your social activity factors into the determination of your creditworthiness. This dynamic could lead to changes in who we let into our social networks and influence who we friend or accept as a connection. Will you decline requests from family members based on your perception of their financial circumstances? “Sorry, Grandma, I love you but I can’t accept your friend request. Your lack of upward mobility might ruin my chances of getting a loan.” 

Continuing this logic, if we start evaluating friend requests against financial consequences, we reach a point where these platforms are no longer social. Rather than serving as welcoming environments for sharing news, posting milestones, and exchanging ideas, our social spaces may simply become extensions of our professional lives–carefully curated and impersonal by necessity. Call it the LinkedIn-ification of all social media.

Then there’s the issue of how much control we have over how our data is used. If social media companies themselves partner with lenders to assess creditworthiness via online profiles, we will be forced to make decisions about how we use social platforms and whether the potential financial benefit is worth a sacrifice in privacy and freedom of choice. 

We’ve focused on social media here, but there are other online behaviors being evaluated in similar ways. Some lenders look at people’s typing patterns, device use, and online behaviors to evaluate whether they’re worthy of a loan. Even the time of day when a borrower requests financing could impact whether they’re approved. A small business owner who applies for a loan at “4 a.m. could be a signal of desperation” and therefore a higher risk than someone who applies during standard operating hours.  

The only thing that doesn’t change is change 

The use of social media activity in lending illustrates interesting yet problematic ways in which our online and offline lives are merging. This convergence is exciting and offers the prospect for new consumer-friendly financial products and an overall boost in convenience. The potential is there for these new products to prove beneficial in ways we can’t yet imagine. 

But as in all areas where new digital technologies intersect with our lives, we must be mindful of how these shifts impact our privacy along the way.