Work from Home: Trust but Use Monitoring Software
May 19, 2020
As the COVID-19 pandemic keeps offices closed and employees continue to work from home, bosses want to be sure their subordinates are working. According to the Washington Post, bosses are “replicating the office” using webcams, microphones, and surveillance software says the article, “Managers Turn To Surveillance Software, Always-On Webcams To Ensure Employees Are (Really) Working From Home.”
Harking back to the chatrooms of yesteryear, employees log into digital work spaces with customizable avatars and chatroom cubicles with instructions to keep webcams and microphones on all day. The idea of the digital workspace designed by Pragli will encourage spontaneous conversation. Some quickly adapt to the technology change, others have difficulty.
While some companies do not replicate the office with programs, they are using other tools such as always on webcams, check-ins, and mandatory digital meetings. There is the concern that companies are being invasive:
“Company leaders say the systems are built to boost productivity and make the quiet isolation of remote work more chipper, connected and fun. But some workers said all of this new corporate surveillance has further blurred the lines between their work and personal lives, amping up their stress and exhaustion at a time when few feel they have the standing to push back.”
Since the COVID-19 forced the American workforce into quarantine, companies want to confirm their workers’ productivity and report on how they are spending their business hours. There has also been an increase in the amount of time Americans spend working each day.
InterGuard is a software that can be hidden on computers and creates a log of everything a worker did during the day. The software records everything a worker does as frequently as every five seconds. It ranks the apps and Web sites as “productive” and “unproductive,” then tallies a “productivity score.”
Many employees do not like the surveillance software and cite that the need to confirm they are actually working disrupts their work flow. Pragli, on the other hand, says the replication of human interaction brings employees closer and allows them to connect more frequently.
A new meaning for the phrase “trust but verify.”
Whitney Grace, May 19, 2020
Content Marketing: The Faux Monte
May 8, 2020
I wrote about the SEO hustle email I received on April 30, 2020. That email became the subject of the conversation I had with the former CIA professional, Robert David Steele. He interviewed me and posted the video from his Web site PhiBetaIota.net. You can view the video at this link. In this post, I want to call attention to the SEO expert’s example blog content, thoughtfully provided by an individual named Christian Arriola and using the alias of a person named Jeffrey Garay. The blog in question is part of a kitchen remodeling business doing work in Pearland near Houston and Allen near Dallas.
The blog post is “How to Get Your Dream Kitchen Remodel Without Breaking the Bank.” Here’s an example of the content which the outfit Woobound wanted to provide to Beyond Search / DarkCyber:
When you have an excellent suggestion of what you desire, take a seat and also write a great breakdown of jobs that you desire finished. You do not need to be technological and also you do not need to make use of building terms yet simply state all the important things you desire a service provider to do and also bid. It can be as easy as: eliminate all existing floor covering and also closets; mount brand-new floor covering, cupboards, kitchen counters, sink as well as home appliances per the strategy; paint; attach sink pipes; as well as mount brand-new lighting fixtures.
It appears that the connection between Beyond Search / DarkCyber is that the root “techno*” appears in the paragraph above and some of Beyond Search / DarkCyber’s more than 18,000 articles. I may be missing other, more sophisticated connections, but on the surface, the idea that kitchen remodeling and the topics in Beyond Search / DarkCyber are tenuously related. Oh, wait, I do cover cyber crime, perhaps that is the hook?
The blog features some broken image links, an 888 number to contact the firm, and a content pool exactly one post deep.
My concern about search engine optimization’s latest “trick” is that some people will accept this “link trade” or “backlink” pitch.
Meaningless links are not helpful to a user. We will be monitoring this ploy because deception is a precursor of cyber crime. Our objective is to take a close look at this faux monte. What we see so far is not appealing; in fact, one of the DarkCyber team used the term
Stephen E Arnold, May 8, 2020
Why Search Sucks: The MVP Approach Maybe?
April 13, 2020
I read what seems to be a modern management write up. The implicit idea is that when developing an app or other software, people get excited. The coder or the team thinks of the many nifty things the new gizmo can deliver. What happens? There are Windows 10 and Apple OSX updates that brick a user’s computer? There are services like Quibi which fall over on Day One because scaling didn’t happen. There are other examples ranging from Google’s wild and crazy Zoom killers to Zoom’s encryption which wasn’t and still may not be… encrypted.
“Why We Are Hardwired to Focus on the Wrong Parts of our Product” seeks to explain why flawed apps and software are the norm. Remember? That’s the big hump in the middle of standard distribution. The challenge today is producing software that sort of works; that is, good enough for today’s often clueless user.
The write up asserts:
Iterative product development achieves its speed through a Minimum Viable Product (MVP) approach. MVP means taking the possible feature set that could be included in a product, or the possible functionality a specific feature could deliver, and cutting it down to the minimum needed to bring value to the end-user.
The consequence of MVP: The bell curve of failure.
The MVP process primes us to want to regain the value we believe we’ve lost. As soon as the product is live, we fall into a weakness-based, additive strategy, where we are compelled to add new functionality in order to win back our lost value (real or imagined).
This weakness-based mindset gets further reinforced when we start analyzing data and feedback. Because loss aversion causes us to focus on losses more than gains, we are more likely to gloss over positive signals and areas of strength and focus instead on the areas of the product that “aren’t working.”
What’s the fix? Here you go:
Analyze what works
Move from addition to subtraction
Understand your strengths.
Sound too good to be true? Well, the approach may be good enough. I am waiting for a book called Thinking Wronger: A Basic Guide.
Stephen E Arnold, April 13, 2020
WFH WTF: A Reality Check for Newbies
March 30, 2020
On Sunday, my son who provides specialized services to the US government and I were talking about WFH or work from home. WFH is now the principal way many people earn money. My son asked me, “When did you start working from home?” He should have remembered, since he was a much younger version of his present technology consulting self.
The year was 1991 (nearly three decades, 29 years to be exact and I am now 76), and I had just avoided corporate RIFFing after an investment bank purchased the firm at which I served as a reasonably high ranking officer. I pitched a multi year consulting deal with the new owners (money people), and I decided that commuting among my home in Kentucky, the Big Apple, and Plastic Fantastic (Silicon Valley) was not for me.
I figured I had a few years of guaranteed income so I would avoid running out an leasing an office. No one who hires me cares whether they ever see me. I do special work; I don’t go to meetings; I don’t hang out at the squash club or golf course; and I don’t want people around me every day. In Plastic Fantastic, I requested an inside office. The company moved the fax machine, photocopier, and supply cabinet to my outside office with lots of windows. I took the dark, stuffy, and inhospitable inside office. Perfect it was.
The seven deadly sins of working from home: [1] Waiting for the phone to ring or email to arrive, [2] eating, [3] laziness, [4] anger, [5] envy, [6] philandering online or IRL, [7] greed. For the modern world I would add social media, online diversions, and fiddling with gizmos.
Why is this important for the WFH crowd?
The Internet is stuffed with articles like these:
- “How To Stay Productive If You’re WFH Because Of The Coronavirus,” which offers tips for WFH by a personal branding expert who convinced Forbes Magazine (the capitalist tool) that either his insights or his money would facilitate a super duper write up
- “WFH Tips I’ve Learned after Working from Home for 12 Years,” essentially insights like “drink water throughout the day and don’t forget to eat.”
- “WFH with a Roommate or Loved One? 5 Ways to Avoid Killing Each Other,” a write up from a real news outfit. An example of the insights delivered is “Be sound conscious.”
The WFH articles I scanned — reading them was alternately amusing and painful — shared a common thread. None of them told the truth about WFH.
My son suggested, “Why not write up what’s really needed to make WFH pay off?” Okay, Erik, here’s the scoop. (By the way, he has implemented most of these behaviors as his technology consulting business has surged and his entrepreneurial ventures flourished. That’s what’s called “living proof” or it used to be before Plastic Fantastic speech took over discourse.)
Discipline. Discipline. Then Discipline Again
The idea is that one has to establish goals, work routines, and priorities. The effort is entirely mental. For nearly 30 years, I follow a disciplined routine. I am at my desk (hidden in a dark, damp basement) working on tasks. Yep, seven days a week, 10 hours a day unless I am sick, on a much loathed business trip, or in a meeting somewhere, not in my home office). Sound like fun? For me, it is, and discipline is not something to talk about in marketing oriented click bait articles. Discipline is what one manifests.
Duh Report: Smart Software Creates Change
March 28, 2020
Another report from the edge of the obvious:
New technology changes lives. Duh.
Not exactly a news flash. But some are surprised. Ali Jazeera explores how artificial intelligence is changing modern society in the article, “Dataland: The Evolution Of Artificial Intelligence And Big Data.”
Classic science fiction generally takes an analog approach to futuristic technology as the concept of a digital landscape was not in the human scope. Our digital data is as identifiable as our fingerprints and different organizations use it to track us. In democracies, it is mostly used to sell products with targeted ads, while authoritarian governments use it to track their citizens’ locations and habits.
Dataland is a documentary that tracks how AI is used in different countries:
“Dataland illustrates the different facets of big data and artificial intelligence being unleashed by the world’s most prolific data scientists. The film goes to Dublin where artificial intelligence is becoming an increasing influence on community life; to Finland where citizens transmit their DNA to improve public health and predictive medicine; and finally to China where facial recognition is routinely used by the state to track the movement, habits and private lives of common people.”
It is inspiring and startling to see how different societies use AI. We literally can only imagine how AI will be used next, then the technologists will make it a reality. It is only a matter of time (years or decades?) before AI is as common as mobile devices.
Interesting source too.
Whitney Grace, March 27, 2020
Acronym Shadow: Good Enough Presages the Future of US Technical Capabilities
February 6, 2020
Apps are nothing but drag and drop programming. The database stuff? A no brainer for Shadow. What other half informed generalizations contributed to the technical, managerial, and political issues with the Iowa caucus app. The New York Times, definitely a paragon of technical acumen, analyzed the situation. Navigate to “The App That Broke the Iowa Caucus.” Remember the NYT was the outfit that fumbled its original online play, ably directed my Jeff Pemberton—what, 40 years ago?—and then lost revenue by pulling its “exclusive” from the LexisNexis service a few years later. Now the NYT is a techno master, happily pointing out that failure took place.
There was no mini failure. Maybe some underhanded activity, maybe some carelessness, and maybe some “we’re experts and know what to do” thinking going on.
DarkCyber believes that the misstep, if that’s what it was, was a reminder that technical expertise and excellence are not as easy as writing a proposal, pulling some influence strings, or assuming that code actually works in the real world.
Nope, the good enough approach is operating.
But the larger message is that if the US expects to maintain a place among technology leaders, a different mind set is needed.
What is that mind set? For starters, big thinkers and MBA types must recognize that planning, attention to detail, quality checks, live tests, and making software usable are necessary.
A failure in a core democratic process is a signpost. For anyone who believes the baloney manufactured about artificial intelligence, natural language processing, and advanced analytics—good enough is not.
Is this a bright signal that American technologists cannot deliver when it matters and when those who seek to disrupt America are getting the clown show of a lifetime.
Stephen E Arnold, February 5, 2020
Another Google Gaffe?
December 30, 2019
Censorship is an intriguing job. A human — chock full of failings — has to figure out if an object is offensive, defensive, or maybe-sive.
If true, the BBC story “YouTube Admits Error over Bitcoin Video Purge” documents a misstep. DarkCyber loves the GOOG, and the research team doubts any anecdote suggesting a Google gaffe took place. For example:
Many video-makers have complained that YouTube’s current systems let so-called “copyright trolls” make false claims on their videos, while its automated detection tools often fail to understand when material has been legally used.
The BBC reports:
YouTube said in a statement that it had “made the wrong call” and confirmed that any content mistakenly removed would be restored. “With the massive volume of videos on our site, sometimes we make the wrong call,” it said.”When it’s brought to our attention that a video has been removed mistakenly, we act quickly to reinstate it.” It said there had been no changes to its polices, and insisted there would be “no penalty” to any channels that were affected by the incident.
I liked the idea that Googzilla is an it, very 2020. And the individuals who depend on YouTube for some money.
Yeah, well, you know, err.
Stephen E Arnold, December 30, 2019
YouTube: Will It Continue to Fancy Dance to the Editorial Control Be Bop?
September 20, 2019
Kids these days have ambitions of being astronauts, writers, scientists, and YouTubers. YouTubers are social media influences with mass followings that make decent livings through YouTube, mostly through ad revenue. YouTubers love and hate their platform of choice and it does not come as a surprise due to how controversial YouTube has become. The Guardian runs down YouTube’s recent headlines and spoke with YouTube CEO Susan Wojcicki in the article, “YouTube’s Susan Wojcicki: ‘Where’s The Line Of Free Speech-Are You Removing Voices That Should Be Heard?’”
YouTube faces frequent scandals, involving its creators posting questionable content like hate speech, Holocaust deniers, etc. And there are those pedophiles who communicate in the comments of children’s videos or engage in code speak related to videos posted by a doting parent for digitally aware Silver Surfer.
YouTube made some progress with anti-hate speech policies to curb hate mongering videos and periodic takedowns. YouTube allegedly has a 10,000 alert, morally upright, dedicated human moderators working with smart software and systems able to the alleged five hundred hours of video posted every minute. Wojcicki seems to say her Googley unit cannot catch every instance of hate speech and questionable video, but they are trying and making a good effort at it.
The video streaming platform is one of the most popular ways Americans entertain themselves and generate money for the online ad giant. The problem is these scandals and bad actor videos that stain YouTube’s reputation, but does removing/banning them violate free speech:
“But hasn’t it been dangerously influential? [Wojcicki] pauses. ‘Look, [these question videos are] a very small percentage of our views, and the way that we think about it is: ‘Is this content violating one of our policies? Has it violated anything in terms of hate, harassment?’ If it has, we remove that content. We keep tightening and tightening the policies. We also get criticism, just to be clear, [about] where do you draw the lines of free speech and, if you draw it too tightly, are you removing voices of society that should be heard? We’re trying to strike a balance of enabling a broad set of voices, but also making sure that those voices play by a set of rules that are healthy conversations for society.’”
This particular write up adds a human dimension to the problem of hate speech and child abuse. Wojcicki’s life includes hobbies. (Imagine. A hard working Type A Googler having a hobby.) She is determined to leave a strong legacy and wants to influence more women to work in the technology industry. A good attitude is a plus when working for a company whose top lawyer makes headlines about personal behavior and the video content contains some darned awful data.
YouTube would have made a great MBA case study had not the market for MBAs imploded and free online classes demonstrated that MBA students go to school for contacts, not learning.
Nevertheless, a great case study awaits.
Whitney Grace, September 20, 2019
YouTube May Be Too Big to Monitor or Fail
September 17, 2019
A friend if mine who shall remain nameless, but who is a Baby Boomer and not technology illiterate once said that the United States government should just shut down the entire Dark Web. I burst out laughing at this statement and incredulously he asked why I guffawed. After explaining how wide spread the Dark Web is, the number of countries involved, and using the “herding cats” metaphor my point was made. Google is facing the same problem as it tries to sanitize YouTube, you can read the story from IT Wire.
YouTube is a big Web site and its expanse does not know an end. Google’s CEO Sundar Puchai stated to CNN that it was too difficult to clean up the entire video platform. YouTube tends to obey the US’s First Amendment Right to Freedom of Speech, but there is a mega backlash when it comes to YouTube hosting harmful content.
The definition of “harmful and malicious” content varies. The general consensus is videos related to neo-Nazism, white supremacy, racist, nudity, promoting terrorism, sexism, hate speech, and anything that specifically targets ethnic or social groups in a negative fashion fits the harmful definition.
Pichai said that using a combination humans and machines Google has gotten 99% of YouTube sanitation right, but videos still sneak between the upload cracks. This reminds me of Web filters “supposed’ to protect children from harmful Internet content, but they always took things to the extreme. Pichai admitted that while he wants the harmful content on YouTube to be well below 1%, he admitted that any large scale system will have a trace amount of fraud, take credit cards for example. Pichai remained silent when confronted with a conspiracy question:
“Asked why YouTube had taken nearly seven years to remove videos claiming that the massacre of children at Sandy Hook Elementary School in Connecticut in 2012 never took place, Pichai did not give a straight answer, but danced around, saying he wished that the company had gotten to the task of removing such videos much earlier. The Google chief was not asked about the fact that numerous alternative media sites have now been demonetized as a result of the purge of content which Google says is unsuitable for YouTube.”
Yep, impossible.
Whitney Grace, September 17, 2019
Machine Learning Created A Big Data Problem And Only Machine Learning Can Fix It
September 12, 2019
Companies heavily invest in machine learning algorithms, but they soon learn that the algorithms are not magic and do not deliver the desired business insights. Data scientists are then employed to handle junk data and “fix the problem,” but they hardly get to use their skills appropriately. The bigger problem, said Silicon Angle’s article, “The Real Big-Data Problem And Only Machine Learning Can Fix It” is that businesses do not employee machine leaning algorithms from the onset. Instead they concentrate on the end result and data quantity over quality, most of which is useless.
Tamr Inc. CEO Andy Palmer and its chief technology officer Michael Stonebraker believe that smaller startups offer more scalable big-data solutions for companies than the legacy companies. Tamr Inc. assists companies to use machine learning to unify their data silos. Palmer and Stonebraker have worked for years to share the truth about big data. It is better to use machine learning for the menial labor, so that the data can be cleaned and organized before it’s analyzed, marketed, or anything is sold with it.
Becoming entirely machine learning is another problem, but it has more to do with a company’s culture than anything else:
“Machine learning isn’t a silver bullet, Stonebraker conceded. Becoming truly data-driven requires both technological and cultural adjustments. In fact, 77% of surveyed executives said business adoption of big data/AI initiatives is difficult for their organizations, according to a NewVantage Partners LLC study. That’s up from last year despite plenty of new software flooding the market. These executives cited a number of obstacles holding back adoption, 95% of which were cultural or organizational, rather than technological. ‘Organizations … need a plan to get to production. Most don’t plan and treat big data as technology retail therapy,’ Gartner Inc. analyst Nick Heudecker has said.”
The culture is one reason why data scientists are forced to spend much of their time sifting and sorting the data. It also means replacing humans with machine learning. Will organizations have the knowledge to make this type of shift in an informed manner?
Whitney Grace, September 12, 2019
-
- Subscribe to Beyond Search
Feature archive
News archive
-
