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PEW Research: Tech Saturation, Well-Being and (my) Remedies

May 29, 2018 By brenda michelson

[Moved from brendamichelson.com. Original publish date: May 29, 2018]

Back in January, I was asked to participate in PEW Research’s survey on the impact of digital life:

“Over the next decade, how will changes in digital life impact people’s overall well-being physically and mentally?”

The choices: more helped than harmed, more harmed than helped, not much changed.

PEW and partner Elon, published comprehensive results of the survey in April:

“Some 1,150 experts responded in this non-scientific canvassing. Some 47% of these respondents predict that individuals’ well-being will be more helped than harmed by digital life in the next decade, while 32% say people’s well-being will be more harmed than helped. The remaining 21% predict there will not be much change in people’s well-being compared to now.”

I was amongst the optimists, more helped than harmed. Though, I thought about the ills — tech addiction, inequality, algorithmic bias — before answering. For me, the opportunities brought by connection and crucial intelligence outweigh the bad. Plus, we can fix the bad.

As with all PEW/Elon studies, respondents were asked for supporting commentary on their choices. Ten themes emerged:

For detailed responses, many named, some anonymous, see the research report.

Regarding fixing the bad, the survey asked:

“what might be done to diminish any threats to individuals’ well-being that are now emerging due to people’s choices in creating digital systems and living digital lives”

Five themes emerged:

I was pleased to see my response make the report, as it validates my current (and future work): intersecting arts, tech and information to make technology knowledge and participation more accessible.

The first part was rolled into “reimagine systems”. No surprise to anyone who has heard my STEAM pitch:

Brenda M. Michelson, an executive-level technology architect based in North America, commented,

“We need to improve how we build and introduce digital products, services, information and overall pervasiveness. On building, we need to diversify the teams creating our digital future. 1) These future builders must reflect society in terms of race, gender, age, education, economic status and so on. 2) As digital is integrative – technology, data, arts, humanities, society, ethics, economics, science, communication – the teams must be composed of individuals from across professions and backgrounds, including artists, scientists, systems thinkers and social advocates. On introduction, we need – desperately – to build information literacy and critical- thinking skills across the population and improve curation tools without impinging on free speech.”

The second part, deep in the report supplement, was rolled into “redesign media literacy”:

“We need (desperately) to build information literacy and critical-thinking skills across the population and improve curation tools without impinging on free speech. Broad education on information literacy and critical thinking can help people discern the validity of information, view multiple sides/perspectives of an issue and consider the motivations of content creators/providers. There should be a developing/refining of our individual habits. Turning off notifications. Giving ourselves digital breaks with other people, doing outdoor activity and so on. Essentially, regaining our attention. As well, we can choose devices and interfaces that augment our everyday experiences while being a present participant in social/work/family situations.”

The report is a truly interesting read. A variety of perspectives from leading thinkers and innovators in our field. Rounded out with regular folks, like me.

Filed Under: trends

Forrester’s Empowered: Workplace HEROes + DIY Technology = Recipe for Shadow IT Disaster, or Front-Line Innovation?

October 10, 2010 By brenda michelson

Like many with corporate IT backgrounds, I find the do-it-yourself (DIY) technology movement simultaneously intriguing and frightening. Intriguing, because of the ease of connecting with co-workers, partners, customers and information to solve problems, improve interactions and advance the business.  Frightening, because I’ve lived through (barely) the data, network and integration nightmares brought on by islands of Access, Excel, FileMakerPro, Visual Basic, etc.

Of course, today’s DIY technologies – Smart mobile devices, Pervasive video, Cloud computing services and Social technologies – are exponentially more powerful than their office productivity predecessors.  Therefore, they must be exponentially more troublesome, right?  Well, that depends.

In Empowered, a new book by Josh Bernoff (co-author of Groundswell) and Ted Schadler of Forrester Research, the authors address this very challenge, how to balance front-line innovation with back-room risk management.  Or, as the authors describe it, changing the way your business runs to harness the power of HEROes: highly empowered and resourceful operatives.

Following an attention grabbing introductory section, the book’s guidance is presented in two more parts.  In part two, the authors focus on HERO projects, describing opportunities and challenges, elucidating with real-world examples, sharing tools and walking through a four-step process to match-up with that other critical DIY base, your empowered customers.

A helpful tool is the HERO Project Effort-Value Evaluation.  After answering a series of questions on a potential projects effort and value, you calculate your projects EVE score.  Scores fall into one of six categories, from no-brainer (value exceeds effort by 25 points) to shadow IT (high effort).  On the Shadow IT projects, the authors don’t say never, however they point out the risk factors, success impediments, and advise collaboration with senior management and IT.

In part three, the authors discuss how management, information technology and HEROes work together to achieve that all important opportunity-risk balance.

The critical concept in part three is the establishment of a HERO Compact.  The HERO Compact is an accord between management, information technology and HEROes, guiding each group’s behavior to make “HERO-powered innovation successful”.

In the spirit of empowerment, I’ve clipped the high-level HERO Compact from Amazon’s Search Inside this Book.

The chapter continues with specific pledges for IT, management and HEROes.  Each pledge reinforces that success requires individual responsibility, collaboration and trade-offs.

For example, the IT Pledge includes: “I will respect requests for new technology support and find ways to say, “Yes, and” rather than automatically saying “No.”.

The HERO Pledge includes: “If my projects entail a significant effort, I will work with my managers and IT to better understand the long-term impact of those projects”.

And the Management Pledge includes: “I will respect assessments of technology risk in HERO projects and work with IT and others to quantify, mitigate and ultimately manage that risk”.

Empowered does a nice job of describing the compelling workforce and customer benefits of embracing DIY technologies, while painting a realistic view of the traps and risk, and offering pragmatic advice and tools for prospective HEROes, managers and IT to co-create a front-line innovation environment.

Organizations struggling to keep up with their customers, employees or competitors on the DIY technology revolution need to read Empowered and think seriously about HERO Compacts.

[Disclosure: Forrester sent me a free “no obligation” copy of Empowered.]

Filed Under: business, business-technology, cloud computing, innovation, social, trends Tagged With: books

O’Reilly Radar: What is Data Science?

June 3, 2010 By brenda michelson

Mike Loukides has an excellent piece on O’Reilly Radar entitled “What is data science?”  In the article, Loukides covers making data products, the data lifecyle, working with data at scale (Big Data), story telling and data scientists.

Throughout the article, Loukides introduces the reader to many data science concepts, tools, experts and skills.

Calling out several items, I love the “data exhaust” term:

“These recommendations are “data products” that help to drive Amazon’s more traditional retail business. They come about because Amazon understands that a book isn’t just a book, a camera isn’t just a camera, and a customer isn’t just a customer; customers generate a trail of “data exhaust” that can be mined and put to use, and a camera is a cloud of data that can be correlated with the customers’ behavior, the data they leave every time they visit the site.”

I think this “make lemonade” sentiment on data quality is crucial:

“Once you’ve parsed the data, you can start thinking about the quality of your data. Data is frequently missing or incongruous. If data is missing, do you simply ignore the missing points? That isn’t always possible. If data is incongruous, do you decide that something is wrong with badly behaved data (after all, equipment fails), or that the incongruous data is telling its own story, which may be more interesting? It’s reported that the discovery of global warming was delayed because automated data collection tools discarded readings that were too low 1. In data science, what you have is frequently all you’re going to get. It’s usually impossible to get “better” data, and you have no alternative but to work with the data at hand.”

The big data definition is excellent.  It’s about the problem, not the (product) solutions:

“The most meaningful definition I’ve heard: “big data” is when the size of the data itself becomes part of the problem. We’re discussing data problems ranging from gigabytes to petabytes of data. At some point, traditional techniques for working with data run out of steam.”

And the information platforms / dataspaces concept ties to my active information tier:

“What are we trying to do with data that’s different? According to Jeff Hammerbacher 2 (@hackingdata), we’re trying to build information platforms or dataspaces. Information platforms are similar to traditional data warehouses, but different. They expose rich APIs, and are designed for exploring and understanding the data rather than for traditional analysis and reporting. They accept all data formats, including the most messy, and their schemas evolve as the understanding of the data changes.”

If you want to learn something today, read the article. Then bookmark it for future reference.

Filed Under: active information, data science, trends

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Brenda M. Michelson

Brenda Michelson

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