How are alumni networks similar to other professional networks? [...]

Placeholder question

Data Is a Toxic Asset [...]

"Toxic Asset" was a term popularized during the great real estate crash of 2007/8 to describe assets such as high-risk mortgages for which there was no longer a functioning market. These assets add risk to a company's bottom line with no potential benefit (and in the case of some high-risk mortgages, no exit). Recently, security expert Bruce Schneier has argued that data can be seen as a toxic asset.

What all these data breaches are teaching us is that data is a toxic asset and saving it is dangerous.

Saving it is dangerous because it's highly personal. Location data reveals where we live, where we work, and how we spend our time. If we all have a location tracker like a smartphone, correlating data reveals who we spend our time with­ -- including who we spend the night with.

Our Internet search data reveals what's important to us, including our hopes, fears, desires and secrets. Communications data reveals who our intimates are, and what we talk about with them. I could go on. Our reading habits, or purchasing data, or data from sensors as diverse as cameras and fitness trackers: All of it can be intimate.

Saving it is dangerous because many people want it. Of course companies want it; that's why they collect it in the first place. But governments want it, too. In the United States, the National Security Agency and FBI use secret deals, coercion, threats and legal compulsion to get at the data. Foreign governments just come in and steal it. When a company with personal data goes bankrupt, it's one of the assets that gets sold.

Saving it is dangerous because it's hard for companies to secure. For a lot of reasons, computer and network security is very difficult. Attackers have an inherent advantage over defenders, and a sufficiently skilled, funded and motivated attacker will always get in.

And saving it is dangerous because failing to secure it is damaging. It will reduce a company's profits, reduce its market share, hurt its stock price, cause it public embarrassment, and­ -- in some cases -- ­result in expensive lawsuits and occasionally, criminal charges.

All this makes data a toxic asset, and it continues to be toxic as long as it sits in a company's computers and networks. The data is vulnerable, and the company is vulnerable. It's vulnerable to hackers and governments. It's vulnerable to employee error. And when there's a toxic data spill, millions of people can be affected. The 2015 Anthem Health data breach affected 80 million people. The 2013 Target Corp. breach affected 110 million. (Source)

Might we be headed back to what Grace Hopper called (derisively) Defensive Computing?

Serendipitous Exchange [...]

Innovations never happen without good ideas. But what prompts people to come up with their best ideas? It’s hard to beat old-fashioned, face-to-face networking. Even Steve Jobs, renowned for his digital evangelism, recognized the importance of social interaction in achieving innovation. In his role as CEO of Pixar Animation Studios (a role he held in addition to being a cofounder and CEO of Apple Inc.), Jobs instructed the architect of Pixar’s new headquarters to design physical space that encouraged staff to get out of their offices and mingle, particularly with those with whom they normally wouldn’t interact. Jobs believed that serendipitous exchanges fueled innovation.1

A multitude of empirical studies confirm what Jobs intuitively knew.2 The more diverse a person’s social network, the more likely that person is to be innovative. A diverse network provides exposure to people from different fields who behave and think differently. Good ideas emerge when the new information received is combined with what a person already knows. But in today’s digitally connected world, many relationships are formed and maintained online through public social media platforms such as Twitter, Facebook and LinkedIn. Increasingly, employees are using such platforms for work-related purposes.3 (Source)

Related: Why Learning Networks Must Be Open Networks

What is a Personal Learning Network? [...]

A good summary of a PLN.

Good learning networks are not necessarily big, but are broad and well chosen.

Why Learning Networks Must Be Open Networks [...]

The bottom line? According to multiple, peer-reviewed studies, simply being in an open network instead of a closed one is the best predictor of career success. In the chart, the further to the right you go toward a closed network, the more you repeatedly hear the same ideas, which reaffirm what you already believe. The further left you go toward an open network, the more you’re exposed to new ideas. People to the left are significantly more successful than those to the right. In fact, the study shows that half of the predicted difference in career success (i.e., promotion, compensation, industry recognition) is due to this one variable. (Source)

Open Networks promote Serendipitous Exchange

Bowling Pin Strategy [...]

Term from Moore on how to solve the chicken-and-egg problem of some products.

The idea is that people won't use your product until other people are using it. Even for something like Microsoft Word, utility is tied to how many *other8 people have Word.

The solution is to find small, niche market segments where people are interconnected enough in a group small enough that broad adoption of a product is possible.

Network Effects presentation (Link)

Losing the Forest in the Digital Trees [...]

New study suggests that we are losing the forest for the trees when we read digitally.

There are several explanations for why mobile digital technologies may prime or trigger a lower-level, concrete mindset in individuals. As noted earlier, prior work has shown that even brief experiences with digital technology for newcomers can have significant effects on neural networks associated with working memory and rapid decision making. Likewise, a growing number of accounts attest to particular information processing habits, such as quick scanning and skimming [4, 24], and expectations, such as immediate gratification, that individuals come to associate with their interactions with digital platforms [18]. The ever-increasing demands of multitasking, divided attention, and information overload that individuals encounter in their use of digital technologies may cause them to “retreat” to the less cognitively demanding lower end of the concrete-abstract continuum. The present work suggests that this tendency may be so well-ingrained that it generalizes to contexts in which those resource demands are not immediately present.

These results are not intended to be an indictment of digital technology and its impact on cognition. Indeed, there is great value in utilizing lower-level, concrete construals of information, particularly in domains requiring the careful consideration of lower-level details, such as analytical problem solving [6] and risk assessment [11]. At the same time, if the increasing accessibility and ubiquity of digital technologies is causing a shift toward the prioritization of concrete construals of information, it is important to consider the ramifications of this trend. Thus, the present work may provide an impetus for HCI designers and researchers to consider strategies for encouraging users to see the “forest” as well as the “trees” when interacting with digital platforms.

Imagined Audience on Social Network Sites [...]

The findings reveal that even though users often interacted with large diverse audiences as they posted, they coped by envisioning either very broad abstract imagined audiences or more targeted specific imagined audiences composed of personal ties, professional ties, communal ties, and/or phantasmal ties. When people had target imagined audiences in mind, they were most often homogeneous and composed of people’s friends and family. (Source)