Policeware and Intelware: Change Underway, Pushback Likely
April 29, 2020
Law enforcement and intelligence are tricky subjects. For decades, the work of government employees and the specialized firms supporting sensitive operations have worked to stay out of the headlines. The spotlight was for rock stars and movie icons, not for investigators, security, and intelligence professionals.
Most of the companies in what I call the policeware and intelware markets have to and prefer to work with people who have been in their foxhole. The result has been the equivalent of a stealth market sector. The clients — traditionally government agencies — like the low profile approach as well. Many of the activities of these professionals and the firms supporting their operations are in a position of considerable risk.
But that seems to be changing. Recent examples include:
Cellebrite’s Covid campaign. The idea is that specialized mobile phone analysis tools can assist with the pandemic. You can read about this in “Cellebrite Pitching iPhone Hacking Tools As a Way to Stop COVID-19.”
A lone wolf employee. You can learn that the NSO Group finds itself in the middle of another PR issue. You can read about this challenge in “NSO Employee Abused Phone Hacking Tech to Target a Love Interest.”
A little known past of a high profile innovator. The somewhat unusual company Banjo finds itself in the spotlight over the allegations made about the firm’s founder. You can read about this in “CEO of Surveillance Firm Banjo Once Helped KKK Leader Shoot Up a Synagogue.”
These examples — if accurate and verifiable — suggest that Silicon Valley attitudes have penetrated the developers of policeware and intelware.
The majority of the companies providing specialized services are probably operating in a reasonably responsible way. Today policeware and intelware have become a multi billion dollar a year market. Most people will never encounter outfits with names like Elbit, Gamma or iCarbon X, and hundreds of others.
The fact is that the behaviors of a small number of companies is causing the policeware and intelware vendors to become the stuff of the talking heads on televised news programs, the launch pad for tweets and blog posts, and a source of embarrassment for the government entities relying on these companies and their products.
What troubles DarkCyber is that an increasing number of vendors of specialized services have realized that many government functions cannot operate without their expertise, products, and engineering. Consequently, what I call “high school science club management” has pushed aside the traditional methods of generating revenue.
Now policeware and intelware vendors offer podcasts, assuming that investigators and intelligence professionals have the time and interest to listen to marketing information about the latest and greatest in graph generation, analytics, and visualization.
There are experts who want to build their own book and training businesses. In the last three days, I have received a half dozen email blandishments to attend this free webinar or download that list of OSINT tools.
What’s next?
Google online advertising to get me to license Blackdot, Qwarie, and Vesper technology?
Here’s the problem:
There are too many companies chasing available policeware and intelware dollars. Established vendors capture the significant projects; for example, Darpa awarded a hefty machine learning contract to BAE Systems, one of the go-to vendors of advanced technology to defense, law enforcement, and intelligence entities.
But every dominant vendor like BAE Systems, there are dozens, if not hundreds, of smaller firms vying to contract. These smaller firms usually work within the procedures which began taking shape in World War II, largely influenced by countries like Britain and several others.
The new companies appear to support the Facebook- and Google-type approach to business. From move fast and break things to digital misdirection, the approach to generating revenue from LE and intel related products and services is shifting. Forget the low profile, off the radar approach. Today it is big trade show booths, podcasts, videos, webinars, and increasingly Madison Avenue style marketing.
Not surprisingly, the three examples cited in this essay are quite different. Cellebrite is virtue signaling. NSO Group is struggling with a lone wolf action. Banjo is dealing with a founder’s youthful dalliance with distasteful activities.
It is indeed risky to generalize. Nevertheless, something is happening within the policeware and intelware market sector. I cannot recall a cluster of news events about LE and intel service providers which startle and surprise in a triple tap moment.
Is there a fix? I want to be positive. Other firms in this sector have an opportunity to assess what their staff are doing with products and services of a quite special nature. Like the nuclear industry, great management effort is needed on an ongoing basis to ensure that secrets remain secret.
The nuclear industry may not be perfect. But at this moment in time, policeware and intelware vendors may want to examine the hiring, management, and institutional approaches in use for decades.
Regulation may be useful, but policeware and intelware is a global activity. Self-control, ethical behavior, and tight management controls are necessary. Easy to say but tough to do because of the revenue pressure many of these vendors face. Plus, outsourcing means that government agencies often cannot do their work without third party support. There is a weird symbiosis visible today: Funding sources, technologists, enforcement officers, procurement professionals, and managers with an MBA.
Bad actors love these revelations. Each item of information that reveals capabilities, weaknesses, and methodologies helps those who would undertake criminal or deleterious activities.
Unless the vendors themselves button up, the unmentionables will be exposed and flap in the wind.
Stephen E Arnold, April 29, 2020
IBM and Ethical AI: Are Wrong Answers Acceptable? But What Is Incorrect?
April 28, 2020
IBM can be surprising. A new president, the fizzle of IBM Watson’s Houston cancer initiative, and the blaming of the firm’s financial woes on Covid19.
Have these issues dampened IBM’s taste for grandstanding?
“IBM’s Pandemic Plan: Supercomputing, New Inventions and Tracking Employees” illustrates what may be the company’s fresh, new approach to becoming really, really relevant.
According to the write up, IBM signed the Pope’s call for AI Ethics. The IBM executive tapped to be the thought leader for ethics, a murky, contentious Philosophy 101 concept, is John Kelly III, an executive charged with making the IBM Watson Health unit perform like a Seal Team 6 professional.
Here are a couple of observations Mr. Kelly made in an interview, which comprise the core of the article cited above:
Here’s one about the value of AI, supercomputing, and great leadership:
We said, “Here’s more compute power than anybody’s ever had access to, for free: Go find solutions to the problems.” They told us that the rate of discovery is just off the charts.
The only hitch in the git along is that none of the AI wizards, including IBM’s and its computing power, has delivered a fix for the virus. In fact, the lack of tangible results makes the virtue signaling claims of IBM and others look silly.
How about this statement?
The trouble is that when you lift the hood, everybody’s reporting it in a different way. We used artificial intelligence two to four times a day to scrape all of their data, which is in different formats — sometimes it’s an Excel file, sometimes it’s a PDF, sometimes it’s a handwritten piece of paper — we scrape it, and then we post it, just like we post a weather map. We post a coronavirus map by county in the U.S.
The problem is that one of the more useful methods of displaying virus-related data comes from Avi Schiffmann, a teenager in Seattle, developed NCoV2019.live. Also the founders of Instagram have delivered Rt Covid 19, which is quite useful. Neither service has supercomputers, Watson, or the Weather Channel to help. Maybe IBM should hire these people? The bottom-line is that IBM can do sort of what social media innovators and a high school junior did. Come on, IBM.
I circled this IBM statement in yellow:
We’ve taken the position that it has to be an opt-in. We should not — based on those ethical principles from the Vatican — track people’s locations, and I should not try to find out that you were next to Adam last Tuesday night, for example. It’s not ethical.
Maybe Mr. Kelly has not read the email about IBM’s cyber division, checked out the Analyst Notebook feature set, or probed into the IBM CyberTap system? DarkCyber wonders, “Are there different definitions of ethics for each unit of IBM?”
And, finally, this statement is intriguing:
The coronavirus, as bad as it is, it’s not Ebola, as an example.
With research data in flux, it is interesting to consider why an IBM VP would offer this clear differentiation. What other distinctions can IBM draw between Covid19 and Ebola? In fact, what did IBM do in the midst of the Ebola outbreaks?
Is IBM ethical? Just ask one of the professionals over 55 RIFFed in the last few years? Is Watson ethical if it outputs incorrect or misleading information about a cancer protocol? Is it ethical to buy back stock to put a shine on a pick up truck designed to deliver mainframes?
Let’s go back to the teen in Seattle. Maybe he could be hired to put IBM Watson to work?
Stephen E Arnold, April 28, 2020
Another Low Profile, Specialized Services Firm Goes for Mad Ave Marketing
April 25, 2020
Investigative software firm ShadowDragon looks beyond traditional cyber-attacks in its latest podcast, “Cyber Cyber Bang Bang—Attacks Exploiting Risks Within the Physical and Cyber Universe.” The four-and-a-half-minute podcast is the fourth in a series that was launched on April second. The description tells us:
“Truly Advanced Persistent attacks where physical exploitation and even death are rarely discussed. We cover some of this along with security within the Healthcare and Government space. Security Within Healthcare and government is always hard. Tensions between information security and the business make this harder. Hospitals hit in fall of 2019 had a taste of exploitation. Similarly, state governments have had issues with cartel related attackers. CISO’s that enable assessment, and security design around systems that cannot be fully hardened can kill two birds with one stone. Weighing authority versus influence, FDA approved equipment, 0day discovery within applications. Designing security around systems is a must when unpatchable vulnerabilities exist.”
Hosts Daniel Clemens and Brian Dykstra begin by answering some questions from the previous podcast then catch up on industry developments. The get into security challenges for hospitals and government agencies not quite halfway through.
A company of fewer than 50 workers, ShadowDragon keeps a low profile. Created “by investigators for investigators,” its cyber security tools include AliasDB, MalNet, OIMonitor, SocialNet, and Spotter. The firm also supports their clients with training, integration, conversion, and customization. ShadowDragon was launched in 2015 and is based in Cheyenne, Wyoming.
Cynthia Murrell, April 13, 2020
Virus-Inspired Virtue Signaling by Attention Hungry AI Developers
April 22, 2020
An article at HackerNoon describes several uses of AI that have an impact on society—some that went very wrong and some that are going quite right. It ponders “The Future of Artificial Intelligence: To Kill or To Heal?” The article covers the issue of biased AI, using the example of the US criminal justice system. It also discusses the resistance in most countries to governments’ use of facial recognition software. While China’s use of the technology to control its citizens has been largely (and rightly) decried, the write-up asserts it has been very useful in containing the spread of the novel coronavirus in that country. See the article for details. AI has also been helping address the pandemic through the use of machine learning to track disease around the globe. We’re told:
“BlueDot is an AI platform that uses NLP and machine learning to track infectious diseases across the globe. It does this by employing algorithms that rapidly browse a multitude of sources. The algorithms are designed to flag early signs of epidemics. In the last weeks of December 2019, the platform recognized a cluster of ‘unusual pneumonia’ diagnoses in Wuhan, China. A little over a week later, the World Health Organization (WHO) came out with an official statement on the existence of a ‘novel coronavirus’ in a patient in Wuhan. BlueDot isn’t the only AI that can flag areas of concern across thousands of sources. Alibaba, a global E-commerce powerhouse, created StructBERT, which is powered by NLP models. The models are capable of processing viral gene-sequences at a fast rate, as well as screening proteins. Alibaba has put the platform to use in the fight against COVID-19. It is freely available to researchers and scientists who can use the information and technology to speed the development of vaccines.”
Then there is the search for a cure. One recent paper describes a machine learning model from Deargen, a firm out of South Korea. The model has identified four possible antiviral meds that might just mitigate COVID-19. Another paper, this one from Hong Kong’s Insilico Medicine, reveals that firm’s AI platform is busy modeling thousands of novel molecules in the hope of turning up one that can disrupt the virus’ replication.
Keep in mind that there are more AI solutions solving virus problems than DarkCyber can monitor. It is easier to count wonky infection data than get AI to deliver more than lists of probables to investigate.
Cynthia Murrell, April 22, 2020
Virtue Signaling in a Difficult Time
April 21, 2020
I have noticed a number of stories about companies working to keep the current virus at bay. Some are interesting; for example, Johns Hopkins University rolled out its dashboard early in the game. Interesting, right? The approach illustrates how dashboards of data deliver a bird’s eye view of a data set. The Johns Hopkins’ approach omits some data; for example, the rate of doubling per sector, demographic data, and controls to present the data in different graphs. DarkCyber has some questions about the service, but let’s set those aside. The Johns Hopkins’ dashboard scores a 7 on the virtue signaling scale created by the DarkCyber team in a 10 minute Zoom call. DarkCyber is thorough.
How do other virtue signaling services stack up on our scale, with 1 being the most limited and 10 representing a home run data service.
- Elon Musk and his ventilators. According to the Sacramento Bee, the ventilators never arrived. The PR did, however. Mr. Musk asserts he has delivered. The score is 1.
- Google stepped forward and offered virus donations. Sounds good, and Vox reported the generous offer. But wait! Millions in cash? Nope, ad credits. Virtue signaling score: 2.
- IBM created a variation on the Johns Hopkins’ dashboard. The twist to the IBM service was that as one clicked down to a state and then a country, the Big Blue service does not make it easy to back out and look at other data. There’s a work around, of course, but the mainframe crowd seems to shine when it comes to usability and medical information. Virtue signaling score: 2.
What outfit gets a 10? None so far.
There are other examples of virtue signaling, but the message is clear: Seize an opportunity to promote one’s company.
Here’s a virus test quiz:
- What service provides demographic data about those diagnosed with the virus?
- What service breaks down the demographics of those who died from the subsequent downstream effects of the virus?
- Within clusters of deaths, what are the zip codes of the deceased?
Give up. The big dashboard producers are following Elon Musk’s approach: Don’t do the work.
Virtue signaling is a big PR and marketing trend. Good enough as some say.
Stephen E Arnold, April 21, 2020
A Cheerleading Routine for AI
April 3, 2020
We have come across a good example of cheerleading with minimal facts. Rah rah for AI, cries the SmartData Collective in their write-up, “Experts Debunk the Biggest Myths About AI in Business.” Writer Sean Mallon begins by noting how fast the AI market is growing, which is indeed to be expected given recent developments (and hype). He declares the growth is due to businesses that comprehend how powerful a tool AI is. He writes:
“Companies are now increasing the adoption of this technology in a range of different industries, which covers diverse sectors such as healthcare, finance, marketing and more. Through the incorporation of AI, industries have seen major shifts in how they run. While the true potential of AI is now being recognized by businesses from all different sectors, many myths have floated around causing skepticism and unnecessary fear over this transformative technology. If AI is to reach its true potential in businesses across all industries, it’s important to explore, and further debunk, these common misconceptions.”
The piece magnanimously helps any reluctant companies see the light by deflating these “myths:” that AI steals jobs, that AI is hard to integrate, and, most dastardly, that AI may be unnecessary. On that last point, Mallon asserts:
“This is perhaps one of the biggest myths currently circulating around industries today, limiting businesses from unlocking their true potential. AI technology is increasingly becoming a part of daily life, especially in the business sector, boosting its productivity and furthering its growth and success. Companies everywhere are using AI to gain a competitive advantage, helping their business to work smarter and faster than those around them.”
For some, I’m sure that is the case; for others, not so much. Business is just too complex for such absolutes. As always, the best bet is to ignore the hype, know your organization’s needs and the capabilities of available software, and mix and match accordingly.
Cynthia Murrell, April 3, 2020
A Cheerleading Routine for AI
April 2, 2020
We have come across a good example of cheerleading with minimal facts. Rah rah for AI, cries the SmartData Collective in their write-up, “Experts Debunk the Biggest Myths About AI in Business.” Writer Sean Mallon begins by noting how fast the AI market is growing, which is indeed to be expected given recent developments (and hype). He declares the growth is due to businesses that comprehend how powerful a tool AI is. He writes:
“Companies are now increasing the adoption of this technology in a range of different industries, which covers diverse sectors such as healthcare, finance, marketing and more. Through the incorporation of AI, industries have seen major shifts in how they run. While the true potential of AI is now being recognized by businesses from all different sectors, many myths have floated around causing skepticism and unnecessary fear over this transformative technology. If AI is to reach its true potential in businesses across all industries, it’s important to explore, and further debunk, these common misconceptions.”
The piece magnanimously helps any reluctant companies see the light by deflating these “myths:” that AI steals jobs, that AI is hard to integrate, and, most dastardly, that AI may be unnecessary. On that last point, Mallon asserts:
“This is perhaps one of the biggest myths currently circulating around industries today, limiting businesses from unlocking their true potential. AI technology is increasingly becoming a part of daily life, especially in the business sector, boosting its productivity and furthering its growth and success. Companies everywhere are using AI to gain a competitive advantage, helping their business to work smarter and faster than those around them.”
For some, I’m sure that is the case; for others, not so much. Business is just too complex for such absolutes. As always, the best bet is to ignore the hype, know your organization’s needs and the capabilities of available software, and mix and match accordingly.
Cynthia Murrell, April 2, 2020
Smart Software Is Changing Work: But What about Actual Facts? Maybe the Pandemic? Maybe Revenue Misses?
March 31, 2020
“AI Is Changing Work and Leaders need to Adapt” is a remarkable analysis of what seems to be taking place IRL (in real life) as opposed to the Ivory Tower world of a university business school. Just as economic departments missed the boat on certain economic developments, the business schools are doing their best to make statements oddly out of step with what’s shakin’ and bakin’ here and now.
This write up is an excellent example of what happens when data lag behind actual events. The notion of time is a problem for outfits like Google, but one would assume that the esteemed Harvard Business School would be zippier.
The article appeared on March 24, 2020. The information in the report was a “recent survey.” Yep, that date and time thing seems to elude the reader.
What does the article report?
The advent of AI poses new and unique challenges for business leaders.
Who holds this idea?
Harvard business school alumni.
But who, pray tell, gathered the insights from this “elite group”?
The answer is “A team at the MIT IBM Watson AI Lab.”
Now that’s a research team to respect: A frenemy university and a large US outfit which has become a punch line for wild and crazy assertions about Watson, the cancer curing TV game show winner.
Academic excellence? Objectivity? Substantial research achievements?
Let’s look at what’s reported about the survey of the elite, shall we?
ITEM 1: Job Data
our MIT-IBM Watson AI Lab team analyzed 170 million online job posts between 2010 and 2017. The study’s first implication: While occupations change slowly — over years and even decades — tasks become reorganized at a much faster pace.
So the research team examined online classifieds? What percentage were real jobs? What percentage were placed in order to obtain competitive intelligence? What percentage were red herrings intended to identify disgruntled employees? Those job listings appear to have been assumed to be valid. Okay. Let’s move on.
ITEM 2: Training
Millions of workers will need to be retrained or reskilled as a result of AI over the next three years, according to a recent IBM Institute for Business Value study.
What no data? That’s right. The findings are a marketing and PR pitch for another IBM study. My goodness, I used to think the McKinsey Award was a PR play. IBM has upped the ante: Harvard, MIT, and home grown research blend for a “finding.” This is academic excellence? This is intellectual honesty? Yeah, right. Remember MIT accepted funds from an interesting character, and Harvard. Right, Harvard. Fine outfit harboring consultants who do commercial work while conducting “research.”
ITEM 3: Educate
Our research shows that technology can disproportionately impact the demand and earning potential for mid-wage workers, causing a squeeze on the middle class. For every five tasks that shifted out of mid-wage jobs, we found, four tasks moved to low-wage jobs and one moved to a high-wage job. As a result, wages are rising faster in the low- and high-wage tiers than in the mid-wage tier.
Data? Nope. The finding is that graduating from an “elite” school delivers contacts, good employment and investment opportunities, and a lever to widen wage gaps. Do elite managers pay themselves and their colleagues less? But the interesting point is that there are zero data.
But who wrote this marketing fluff? An MIT tenured professor? A team of Harvard elite after making a podcast and enjoying ever so much one another’s company?
No.
The write up was written, according to the article, by Martin Fleming, IBM’s chief economist and vice president.
The survey data? The connection with the real world? Ha ha.
When Mad Magazine went out of business, I wondered what would fill the gap?
I now know. It is smart software, not the pandemic, and the demonstration that economists are as prescient as ever.
Stephen E Arnold, March 31, 2020
Fours Hours to Learn IBM Watson and Microsoft Azure. Believe It or Not. Hint: Not
March 26, 2020
DarkCyber believes that online instructional videos are useful. However, DarkCyber believes that overstatement, hyperbole, and general buzzword craziness undermine the credibility of those offering a program.
An excellent example of basic marketing information packaged like a six figure F.P. Journe Tourbillon Souverain Vertical watch, navigate to “Machine Learning with Watson and Azure.” You can download a four hour chunk of video which presents 20 lectures. That works out to 12 minute videos at which time, you
would be able to develop and deploy your applications over IBM Cloud- Bluemix. and having command over the Watson services and tools available.
Now what will you learn? Here’s the line up:
- Cognitive Computing and how Watson changes the game
- Using Watson Visual Recognition to tag and classify visual content using machine learning
- Capabilities of the Watson API and how to choose the best features for your task
- Using Watson Assistant to build an AI assistant (ChatBot)
- Using Watson Watson Discovery to unlock hidden values to find answers , monitor trends and surface patterns
- Using Watson Natural Language Understanding for advanced text analysis
- Using Watson Knowledge Studio to discover meaningful insights in unstructured text.
- Using Watson Speech to Text to easily convert audio and voice into written text
- Using Watson Text to Speech to convert text into natural-surrounding audio
- Using Watson Language Translator to translate from one language to another
- Using Watson Natural Language Classifier to interpret and classify natural language with confidence
- Using Watson Personality Insights to predict personality characteristics through text
- Using Watson Tone Analyzer to understand emotions and communications style in text
- Text Analytics
- Detecting Language
- Analyze image and video
- Recognition handwritten from text
- Generate Thumbnail
- Content Moderator
- Custom Vision
- Translate
But wait!
The programs will also explain Microsoft Azure services; for example:
- Computer Vision
- Content Moderator
- Custom Vision
- Text Analysis
- Translator.
You will not need an IBM account, but you will need a Microsoft Azure account.
This seems like an interesting program. Perhaps the overselling contributes to some of IBM’s more interesting deployments?
Stephen E Arnold, March 26, 2020
IBM: A Leader in Following?
March 16, 2020
DarkCyber spotted “IBM Prepares To Advance Watson’s Language Ability.” The story appeared in Capital FM, an online publication in Nairobi. That’s okay. What’s interesting is that IBM has announced “the first commercialization of key Natural Language Processing (NLP) capabilities to come from IBM Research’s Project Debater, the only AI system capable of debating humans on complex topics.”
What’s new, aside from the Kenya coverage? Here’s a sampling of the technologies that will allegedly make Watson a superhero: Natural language processing. Watson will understand sentiment which can “identify and analyze idioms and colloquialisms for the first time.” [Emphasis added]
Plus:
IBM is bringing technology from IBM Research for understanding business documents, such as PDF’s and contracts, to also add to their AI models.
Where’s the technology originate? Project Debater. There’s also “deep learning based classification which
can learn from as few as several hundred samples to do new classifications quickly and easily. It will be added to Watson Discovery later this year.
Also, there’s another innovation:
It will also exploit natural language through Clustering or Advanced Topic Clustering. Building on insights gained from Project Debater, new topic clustering techniques will enable users to “cluster” incoming data to create meaningful “topics” of related information, which can then be analyzed.
Okay, let’s step back. NLP, quick deep learning, clustering, and the other technologies. My recollection is:
- IBM’s Dharmendra Modha was writing about text clustering in “Large Scale Parallel Data Mining” which is about a decade after the Endeca crowd fired up their functional facets for “Guided Navigation”. Now this clustering is coming to IBM Watson. What?
- In 2003 IBM researchers filed a patent application for “US7130777, Method to hierarchical pooling of opinions from multiple sources.” Now Watson is doing what commercial vendors have been offering for many years; for example, Lexalytics in 2003. Not exactly a text book case of using home grown technology or emulating a competitor, is it?
- And NLP dates back to 1993 and the work of Vincent Stanford, Ora Williamson, Elton Sherwin, and Frank Castellucci. See US5615296. These are IBM professionals. And 1993 was more than a quarter century ago.
Net net: Kenya, Watson, and technologies that have been around for decades are part of IBM’s preparations to add functions to Watson. “Prepares”, year, pretty speedy.
Watson? What are you doing? Maybe DarkCyber should ask Alexa?
Stephen E Arnold, March 16, 2020
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