Tuesday, April 23, 2019

Knowledge Worker Productivity Improvements with Machine Learning


Leveraging machine learning to enhance capabilities that can recognize context, concepts, and meaning means there are interesting new opportunities for collaboration between knowledge workers and computational power. For example, Bluedog’s experts can now provide more of their own input for training, quality control, and fine-tuning of algorithm-based outcomes. We use the computational power of our servers to augment the expertise of human collaborators — this helps to create new areas for our experts to leverage.

For example, at Bluedog, we utilize several algorithm-based tools to help us quickly assess opportunities for our clients. We extract information from Word Documents locally for multiple uses. With one tool, we take advantage of each Word document’s XML metadata. From there, we use a regex library to find each targeted word or phrase in the document, then adding them to a list. Our toll then performs for-loops to scan for relevant patterns in the XML to extract data.

Knowledge workers — the staff or consultants who reason, create, decide, and apply insight into non-routine cognitive processes — can contribute to redesigning work process roles and team member roles. Consider financial auditing, where AI is likely to become pervasive. Often, when AI offers a finding, the algorithm’s reasoning isn’t obvious to the accountant, who ultimately must offer an explanation to a client — characteristic of the “black box” problem. To improve this outcome, Bluedog recommends providing an interface so experts to enter concepts they deem important into the system and be provided with a means to test their own hypotheses. In this way, we recommend making models accessible to common sense. 

As cybersecurity concerns mount, organizations have increased the use of instruments to collect data at various points in their network to analyze threats — and to address “Internet-of-Things” (IoT) devices. However, many of these data-driven systems do not integrate data from multiple sources. Nor do they incorporate the common-sense knowledge of cybersecurity experts, who know the range and diverse motives of attackers, understand typical internal and external threats, and appreciate the degree of risk to an organization. 


Bluedog’s experts specify the use of Bayesian models — which employ probabilistic analysis to capture complex interdependence among risk factors —  combined with expert systems judgment. In cybersecurity for enterprise networks, complex factors may include large numbers and types of devices on the network. It is crucial to access the knowledge of the organization’s security experts about attackers and risk profile to better intercept cybercriminals.

Monday, April 22, 2019

SIFT Score - the West's Answer to China's Social Credit Rating. Thanks, Big Brother

Data on what you buy, how, and where is secretly fed into AI-powered verification services, according to the Wall Street Journal. These are supposed to help companies guard against credit-card and other forms of fraud.

More than 16,000 signals are analyzed by a service called Sift, which generates a "Sift score," used to flag devices, credit cards and accounts that a vendor may want to block based on a person or entity's overall "trustworthiness" score. From the Sift website: "Each time we get an event -- be it a page view or an API event -- we extract features related to those events and compute the Sift Score. These features are then weighed based on fraud we've seen both on your site and within our global network, and determine a user's Score. There are features that can negatively impact a Score as well as ones which have a positive impact."

The system is similar to a credit score except there's no way to find out your own Sift score. This sounds a lot like the data that China's social credit system, in part, uses. In the PRC, a person's social score can vary depending on their behavior. The exact methodology is a secret — but examples of infractions include bad driving, smoking in non-smoking zones, buying too many video games and posting fake news online. While Edward Snowden certainly demonstrated the global extent of the US surveillance state, corporate entities have not implemented anything on the level of the Chinese social scoring system. Yet.


Thursday, April 18, 2019

Using Containers for Secure Web Services

Containers are a means to install and run applications in an isolated environment on a server (physical or virtual). The application running inside a container is limited to resources (CPU, memory, disk, process space, users, networking, volumes) allocated for that container. Access is limited to that container’s resources to avoid conflict with other containers. Think of a container as an isolated sandbox for an application to run in.

The concept is similar to virtual machines, but containers use a light-weight technique to achieve resource isolation, whereby they use the Linux kernel (as opposed to a hypervisor-based approach taken by virtual machines). Containers issue Linux commands to make use of a subset of system resources.

Docker is a popular tool to create and start a container. Docker Community Edition (CE) is ideal for developers and small teams looking to get started with Docker and experimenting with container-based apps. It enables packaging of an app with all its dependencies and libraries.
Here’s more information on using AWS to build secure services with containers.


Tuesday, April 16, 2019

End of The Jasons? Who Will Lead if this brain trust is disbanded?

The Department of Defense says is ending a decades-long, open-ended agreement with a legacy science advisory board, a move that has set off alarm bells for some analysts. But the department has not ruled out relying on that office for more information in the future.

The Jasons — an important advisory committee that assessed many difficult issues. Named for Jason of the Argonauts, luminaries on this panel answered (in secret) pressing questions the government had, such as:  Are there UFO? No. Should we nuke Vietnam? Also, no. What is Quantum Computing? Using the spin of quarks like bits. All answered in the 1960s!

As a Federally Funded Research Bureau (FFRB), MITRE doesn’t implement ideas, only the non-profit only consults. After WWII, the government decided it would not be caught with its pants down again (having been severely understaffed after the Depression, at the start of the war). MITRE and other FFRBs are funded as a percent of the total budget — MITRE isn’t taking work from contractors, it is providing neutral oversight and guidance. 

Read more about the Jason at 


Monday, April 15, 2019

This day - April 16, 1178 BCE - was the Return of Odysseus to Ithaca after his Travels

On this day, in 1178 BCE, Odysseus arrived in Ithaca, having begun his way home when the Trojan War ended. He had served ten years as one of the most distinguished leaders of the Greeks. His voyage was fraught with perils: the Cyclopes, Sirens, Scylla and Charybdis, and other obstacles.

Read about it at https://en.wikipedia.org/wiki/Odyssey#Homecoming