innovation

Biometric Identity Theft

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Recently I have been researching the potential of fraud and identity theft using fingerprints from photos posted on social media. Last week Amazon released its “Amazon One” Palm Scanner as a means to pay for purchases when shopping. That announcement made me wonder, what are the potential implications for fraud and identity theft using biometric data taken from images?

Man's forearm and hand, index finger extended to point to one of a series of "digital keys"
Could Photos posted on Social Media sites become the Key to Digital Identify Theft?

There are a surprising number of ways to accurately identify someone from a photo or video. Moreover, there is technology to copy fingerprints from social media photos taken up to three meters away. New technology has been proven effective at using 3D printing technology to create “fake fingerprints” that will bypass many fingerprint scanners.

Technology continues to improve at a rapid pace, which often means, “Where there is the will there’s a way.”

Since fingerprints can be copied from photos taken up to three meters away does that mean a palm print could potentially be copied from a photo taken 5-10 meters away? That question led to an interesting but unscientific experiment where I took pictures of my own hand, enlarged them, and then measured the distance between the ridges and furrows of both my fingers and my palm, and then compared the results of the two. Spoiler – probably not.

There are several areas where that distance was similar for both my fingers and palm. But, there were also areas on my palm where the average distance between “landmarks” was 3-5+ times greater. It turns out that for identification purposes a palm image is often segment into 3-4 distinct regions, likely due to this type of variation. This link was helpful to understand the process.

This research led to an idea for a chip-based embedded filter for smart devices and laptops. It would obfuscate key biometric information when extracting the data for display, without affecting the integrity of the original stored image. This functionality would automatically provide an additional layer of privacy and data protection. It would require optimized object detection capabilities (possibly R-CNN) that were highly efficient, and run on a capable but low energy processor like the Arm Cortex-M. Retraining and upgrades would be accomplished with firmware updates.

Edit 2020-10-13: This article on “Tiny ML” from Medium.com is the perfect tie-in to the idea described above.

While Amazon’s technology is much newer and presumably at least partially based on their 2019 Patent Application (which does look impressive), it makes you wonder how susceptible these devices might be to fraud given reports of the scans occurring “almost instantaneously.” Speed is one aspect of successful large-scale commercial adoption but the accuracy and integrity of the system are far more important from my perspective.

Time will tell how robust and foolproof Amazon’s new technology really is. Given their reach, this could occur sooner than later. Ultimately, multiple forms of biometric scans (such as a full handprint with shape, palm, and fingerprints, or a retina scan 2-3 minutes prior to the palm scan to maintain performance) may be required for enhanced security, especially with mobile devices.

Additional Resources:

IoT and Vendor Lock-in

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I was researching an idea last weekend and stumbled across something unexpected. My personal view on IoT has been that it provides a framework to support a rich ecosystem of hardware and software products. That flexibility and extensibility foster innovation, which in turn fosters greater use and ultimately adoption of the best products. It was quite a surprise to discover that IoT was being used to do just the opposite.

My initial finding was a YouTube video about “Tractor Hacking” to allow farmers to make their own repairs. That seemed like an odd video to appear in my search results, but midway or so through the video it made sense. There is a discussion about not having access to software, replacement components not working because they are not registered with that tractor’s serial number and that the only alternative is costly transportation of the equipment to a Dealership to have a costly component installed.

Image of jail cell representing vendor lock-in
Image Copyright (c) gograph.com/VIPDesignUSA

My initial thoughts were that there had to be more to the story, as I found it hard to believe that a major vendor in any industry would intentionally do something like this. That led me to an article from nearly two years earlier that contained the following:

“IoT to completely transform their business model”   and

“John Deere was looking for ways to change their business model and extend their products and service offering, allowing for a more constant flow of revenue from a single customer. The IoT allows them to do just that.”

That article closed with the assertion:

“Moreover, only allowing John Deere products access to the ecosystem creates a buyer lock-in for the farmers. Once they own John Deere equipment and make use of their services, it will be very expensive to switch to another supplier, thus strengthening John Deere’s strategic position.”

While any technology – especially platforms, has the potential for vendor lock-in, the majority of vendors offer some form of openness, such as:

  • Supporting open standards, APIs and processes that support portability and third-party product access.
  • Providing simple ways to unload your own data in at least one of several commonly used non-proprietary formats.

Some buyers may deliberately make the decision to implement systems that support non-standard technology and extensions because they believe the long-term benefits of a tightly coupled system outweigh the risks of being locked-into a vendor’s proprietary stack. But, there are almost always several competitive options available so it is a fully informed decision.

Less technology-savvy buyers may never even consider asking questions like this when making a purchasing decision. Even technologically savvy people may not consider IoT as a key component of some everyday items, failing to recognize the implications of a closed system for their purchase. It will be interesting to see if this type of deliberate business strategy changes due to competitive pressure, social pressure, or legislation over the coming few years.

In the meantime, the principle of caveat emptor may be truer than ever in this age of connected everything and the Internet of Things.

 

Good Article on Why AI Projects Fail

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high angle photo of robot
Photo by Alex Knight on Pexels.com

Today I ran across this article that was very good as it focused on lessons learned, which potentially helps everyone interested in these topics. It contained a good mix of problems at a non-technical level.

Below is the link to the article, as well as commentary on the Top 3 items listed from my perspective.

https://www.cio.com/article/3429177/6-reasons-why-ai-projects-fail.html

Item #1: 

The article starts by discussing how the “problem” being evaluated was misstated using technical terms. It led me to believe that at least some of these efforts are conducted “in a vacuum.” That was a surprise given the cost and strategic importance of getting these early-adopter AI projects right.

In Sales and Marketing you start the question, “What problem are we trying to solve?” and evolve that to, “How would customers or prospects describe this problem in their own words?” Without that understanding, you can neither initially vet the solution nor quickly qualify the need for your solution when speaking with those customers or prospects. That leaves a lot of room for error when transitioning from strategy to execution.

Increased collaboration with Business would likely have helped. This was touched on at the end of the article under “Cultural challenges,” but the importance seemed to be downplayed. Lessons learned are valuable – especially when you are able to learn from the mistakes of others. To me, this should have been called out early as a major lesson learned.

Item #2: 

This second area had to do with the perspective of the data, whether that was the angle of the subject in photographs (overhead from a drone vs horizontal from the shoreline) or the type of customer data evaluated (such as from a single source) used to train the ML algorithm.

That was interesting because it appears that assumptions may have played a part in overlooking other aspects of the problem, or that the teams may have been overly confident about obtaining the correct results using the data available. In the examples cited those teams did figure those problems out and took corrective action. A follow-on article describing the process used to make their root cause determination in each case would be very interesting.

As an aside, from my perspective, this is why Explainable AI is so important. There are times that you just don’t know what you don’t know (the unknown unknowns). Being able to understand why and on what the AI is basing its decisions should help with providing better quality curated data up-front, as well as being able to identify potential drifts in the wrong direction while it is still early enough to make corrections without impacting deadlines or deliverables.

Item #3: 

This didn’t surprise me but should be a cause for concern as advances are made at faster rates and potentially less validation is made as organizations race to be first to market with some AI-based competitive advantage. The last paragraph under ‘Training data bias’ stated that based on a PWC survey, “only 25 percent of respondents said they would prioritize the ethical implications of an AI solution before implementing it.

Bonus Item:

The discussion about the value of unstructured data was very interesting, especially when you consider:

  1. The potential for NLU (natural language understanding) products in conjunction with ML and AI.
  2. The importance of semantic data analysis relative to any ML effort.
  3. The incredible value that products like MarkLogic’s database or Franz’s AllegroGraph provide over standard Analytics Database products.
    • I personally believe that the biggest exception to assertion this will be from GPU databases (like OmniSci) that easily handle streaming data, can accomplish extreme computational feats well beyond those of traditional CPU based products, and have geospatial capabilities that provide an additional dimension of insight to the problem being solved.

 

Update: This is a link to a related article that discusses trends in areas of implementation, important considerations, and the potential ROI of AI projects: https://www.fastcompany.com/90387050/reduce-the-hype-and-find-a-plan-how-to-adopt-an-ai-strategy

This is definitely an exciting space that will experience significant growth over the next 3-5 years. The more information, experiences, and lessons learned shared the better it will be for everyone.

Apollo 11 50th Anniversary – Interesting photos & article link

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I still remember my parents allowing me to stay up late to watch the first moonwalk. It was 9:30 pm, I was 5 years old, and we were huddled around an old “black and white” television that had a circular viewing area. My parents tried to convey how important and monumental that moment was – telling me that I would be telling this story to my children someday.

What I remember most was being amazed seeing the astronauts hop around with ease Photo - bottomand not understating how that could be. We had watched the launch on TV and were getting updates nightly from Walter Cronkite on the evening news. Normally my dad would sit at a TV table to eat dinner and watch the news as my mom sat with my sister and me at our kitchen table, but this week was different.

With all of the news this past week on the 50th DisplayAnniversary of the first moonwalk it triggered a couple of memories. One of them was that I had a collectible item that I purchased in 2005 at the annual Children’s Circle of Care leadership conference in San Diego, CA. There was a luncheon held on the deck of the USS Midway Museum and afterward, I took a tour. It is an incredible place to visit if you are ever near San Diego.

Before leaving that day I went to the gift shop to get a few trinkets for my wife and children. What I found was a beautiful display, which I immediately purchased and had shipped home. This display was taken to school a couple of times for “show and tell.” It hung on my office wall for 3 years or so and then went into storage with other artwork. It then sat for the past decade and I almost forgot that I had it.

To me, this display is both beautiful to see and very inspirational as well. Human creativity is an incredible thing! As an aside, I have never seen anything like this display so I thought I would share it with you.

Today I also ran across a good article regarding this event that provided information that I had not seen before. It is very interesting and can be found here: https://go.usa.gov/xyVGh

Edit: This was another good article that discusses the advanced flight control computer used at the time – https://www.linkedin.com/pulse/apollo-11-moon-landings-fourth-crew-member-computer-far-fishman/

This anniversary is a great reminder of the power of individuals, teams, and partnerships when they are mission-focused. I find people like the men and women of NASA to be extremely motivational, and the few that I have met have all been very friendly people as well. They are the Humble Heros!SKO Speaker

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Commentary on an HBR article about Start-ups & Entrepreneurship

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A friend posted this article on LinkedIn.com. Due to character limitations for comments, I decided to post my response here. Below is a link to the article referenced: https://hbr.org/2019/07/building-a-startup-that-will-last

The article is interesting, but the emphasis on “second and third acts” assumes that the start-up will successfully navigate the first act. Even with addressing what the author views as key points this is still a very big assumption. The reasons for Longevity and Success are far more complex and multi-dimensional, but it does place a spotlight on some of the more important areas of focus.

Long-term success requires several things: The right combination of having a unique goal that has the potential to make a big impact (think “No software” from Salesforce.com); Innovative ideas to achieve that goal; A diverse team to build the product (a mix of visionaries, insightful “translators,” technical experts, designers, planners, adept doers, etc.); Very good sales / business development / marketing to describe a better way of doing things and converting that to new business; and ultimately a management team focused on sustainable and scalable growth.

The point made about the need to, “Articulate a value framework oriented toward societal impact, not just financial achievement” seems a bit superficial and too tactical in nature.

First, there are unintended consequences to most new technologies. Social Media is a recent example, but Genetic Editing and AI are two areas that are likely to provide more examples over the next decade. Not every societal impact will be positive, and having a negative impact could very well lead to the untimely demise of that company.

Second, the two ideas (societal impact and financial achievement) are not mutually exclusive. When I owned my consulting company we had a goal of funding $1M worth of medical research that would find a cure for Arthritis. We allocated half of our net profits for this goal. Every employee was on-board with this because there was a tangible example of why it mattered (my daughter). We invested $500K, helped launch a few careers for some brilliant MD/Ph.Ds and at least one national protocol came out of their research.

Mission and Vision are so important to a company, yet so many companies fail to view this as anything more than a marketing effort. Those companies fail to realize that this is as much to motivate and inspire their employees, as it is to grab the attention of a prospective customer. These should be both inspirational and aspirational, such as the “BHAG” (Big Hairy Audacious Goals) that Collins and Porras wrote about 25 years ago.

Image of globe with network of connected dots in the space above it.

Regarding Endurance and the assertion that “…the best businesses are intrinsically aligned with the long-term interests of society,” my take is slightly different. The best businesses are always looking for trends and opportunities in an ever-changing global competitive landscape – as opposed to looking to their competitors and trying to ride on their coattails. Companies with a culture of fostering innovation as a way to learn and grow (Amazon and Google are two great examples) are able to find that intersection of “good business” and “positive societal impact.” It is much more complex than a simple one-dimensional outlook.

But, it was a good article to help reframe ideas and assumptions around growth.