Algorithmic zoning, a deputized police chatbot and 10 breakthrough technologies to follow this year — This Week’s 10 Reads from a Chief Innovation Officer

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I read over 100 articles this week so you don’t have to — Here are the top 10 you should read over the weekend and why they matter for the public sector. Let’s dive into this week’s reads —

The Articles —

Out of over 100 articles, here are the top 10 that stood out this week:

🗺 Algorithmic zoning could be the answer to cheaper housing and more equitable cities http://bit.ly/2EPeYp7

🧠 Cognitive technologies: a technical primer http://bit.ly/2FvHUAs

🎧 How UPS delivers faster using $8 headphones and code that decides when dirty trucks get cleaned http://bit.ly/2GyePUc

📸 AI-Aided Cameras Mean No More Car Mirrors, No More Blind Spots http://bit.ly/2o8co44

❤️ Taiwan has figured out how to turn online disagreements into a positive political force http://bit.ly/2Fs0U2L

💡 Why Decentralization Matters http://bit.ly/2EPTkRm

🤖 Los Angeles Chatbot Deputized to Help with Police Recruitment http://bit.ly/2EHQ5IJ

9️⃣ The Nine Elements of Digital Transformation http://bit.ly/2oh2cp0

🚕 Autonomous Taxi Revenues: Who Will Reap the Profits from the Boom… http://bit.ly/2EQcN17

🔍 You’ll want to keep an eye on these 10 breakthrough technologies this year http://bit.ly/2FkrmLJ

The Bottom Line —

Just in case you don’t have time to read each article, here are the key takeaways and why each one matters for government:

🗺 Algorithmic zoning could be the answer to cheaper housing and more equitable cities http://bit.ly/2EPeYp7

🏛 Why it Matters for Government: This was a fascinating read on something called algorithmic zoning — which is a shift from traditional rule-based models (think traditional zoning and land use plans) to “dynamic systems based on blockchains, machine learning algorithms, and spatial data.”Algorithmic zoning on a blockchain would rely on a type of token (similar to bitcoin) that would be used as a currency to incentivize or disincentivize price, utilization and more. For government, using algorithmic zoning could definitely lead to cheaper housing and more equitable cities — but there are challenges with the reality of rolling out such a system. For example, this system would require a critical mass of adoption (bitcoin is still only accepted a few businesses) in order to be useful or effective — and would run into the challenge of creating non-transferrable, silo’d incentive systems across different cities. Regardless of these, there are still elements of this idea that hold value for long-term consideration, such as taking a systems-driven approach to city management.

🧠 Cognitive technologies: a technical primer http://bit.ly/2FvHUAs

🏛 Why it Matters for Government: This was a great breakdown of cognitive technologies today and what’s around the corner for them from Deloitte. A simple Google search will show you that there are countless definitions of cognitive technologies, but I find it best to think about them as a physical platform manifestation of artificial intelligence — meaning, cognitive technologies leverage artificial intelligence to augment or automate human intelligence and tasks.

Cognitive computing (CC) describes technology platforms that, broadly speaking, are based on the scientific disciplines of artificial intelligence and signal processing. (Wikipedia)

In the article, Deloitte outlined four specific categories of cognitive technologies being used today (also in the table below): Robert process automation (RPA), cognitive language technologies, cognitive machine learning, and cognitive computer vision. Each of these categories has the ability to significantly impact government, from automating back-end IT functions (robotic process automation) to making police body cameras a proactive tool to identify threats for officers (cognitive computer vision) — the use-cases are unlimited.

 

Deloitte Insights (2018)

For government agencies, this doesn’t mean you need to widely adopt cognitive technologies — rather, it’s important to understand the bigger picture of where the technology is today and what’s possible. By embracing cognitive technologies, you just might find an opportunity to become a cognitive government.

🎧 How UPS delivers faster using $8 headphones and code that decides when dirty trucks get cleaned http://bit.ly/2GyePUc

🏛 Why it Matters for Government: This was a great read that gave a deep dive into UPS’s data science chops and more importantly, the significant impact of simple fixes. By applying $8 headphones to an existing process, UPS was able to save new recruits from memorizing hundreds of zip codes by audio telling them what conveyor belt to put packages on. Simple fix, major impact. For government agencies, this is a great reminder that as we begin to aggregate and warehouse more of our data — we need to find simple but impactful ways to put this data to work. And it just might be with a pair of $8 headphones.

📸 AI-Aided Cameras Mean No More Car Mirrors, No More Blind Spots http://bit.ly/2o8co44

🏛 Why it Matters for Government: Last week, I shared a post about 73 Mind-Blowing Implications of Driverless Cars and Trucks, and here’s a new one for the list — no need for rear-view mirrors (or any mirrors). This may sound like a something decades away, but Japan already passed a law enabling mirrorless cars on their highways — today. For government agencies, AI blindspot detection and the rise of self-driving cars may lead to cars losing their mirrors — but think bigger picture — if you don’t need to see around your car, do we really need streetlights blanketing long stretches highways with artificial light? Exponential technologies and behavior change will inevitably lead to changes in the existing infrastructure we actually utilize going forward.

❤️ Taiwan has figured out how to turn online disagreements into a positive political force http://bit.ly/2Fs0U2L

🏛 Why it Matters for Government: This was a fantastic read about how Taiwan took unstructured, online disagreements and applied a new technology to turn them into structured data that was much easier to understand and make decisions off of. The technology used, a US-startup called Pol.is, was created to bring “AI & machine learning to participatory democracy.” For government agencies, tools like this will become increasingly important as a way to crowdsource structured data (and eventually microtasks) from the general public today. Traditional social media platforms such as Facebook can amplify hyper-polarization of online dialogs, and don’t provide any actionable feedback — outside of sentiment through emojis 😡. It will be important for government agencies to be an active participant and facilitator of such tools, or they face being constantly disrupted by the collective energy of these groups.

💡 Why Decentralization Matters http://bit.ly/2EPTkRm

🏛 Why it Matters for Government: This was a fascinating look at the role of decentralized systems today — and why they are going to be important platforms of the future. Most of us may have heard of decentralization as a model through the rise of the blockchain, but this is an early look at a future rise of decentralized networks, called cryptonetworks, which have the power to fundamentally reshape the Internet and traditional economic models as we know them.

Cryptonetworks are networks built on top of the internet that 1) use consensus mechanisms such as blockchains to maintain and update state, 2) use cryptocurrencies (coins/tokens) to incentivize consensus participants (miners/validators) and other network participants. (Chris Dixon)

For government, a decentralized future doesn’t have to mean the elimination of government as a middleman, but it does change the role that government and constituents have within a network.

🤖 Los Angeles Chatbot Deputized to Help with Police Recruitment http://bit.ly/2EHQ5IJ

🏛 Why it Matters for Government: We’ve seen many chatbot use-cases for government emerge over the years, but the City of Los Angeles use of Chip (now Officer Chip) is something you should follow. Chip launched last year to help answer questions for individuals interested in starting a business in L.A. through the Los Angeles Business Assistance Virtual Network (BAVN) but in its new role, is now helping answer questions for prospective police recruits.For government, my two main takeaways from this are:

  1. One brand —The City of Los Angeles was smart to keep the Chip name as they expand use-cases for it, thus helping build brand awareness with the public with each interaction. In the future, I can see there just being one Chip that can you can access on any city website that has the ability to interface and respond to any question, even if you’re not on the correct site.
  2. Automating Knowledge — I love the strategy L.A. is using with rolling out their chatbots, by tying them to structured knowledge repositories, it enables them to be accessible 24/7 and frees up valuable staff time spent answering repetitive questions.

In the future, I hope to see Chip expand to be accessible through text messages and other major platforms the population may frequent more than a city website.

9️⃣ The Nine Elements of Digital Transformation http://bit.ly/2oh2cp0

🏛 Why it Matters for Government: This was a great read from MITSloan Mgmt Review that broke down nine elements of digital transformation in companies across three domains: customer experience, operational processes, and business models. For government agencies, we’ve seen year-over-year that constituents expect the same, if not better, service delivery in the public sector then what is received in the private sector [PDF]. Understand the trends and strategies for digital transformation in the private sector provides a great starting point for government agencies interested in doing the same.

🚕 Autonomous Taxi Revenues: Who Will Reap the Profits from the Boom… http://bit.ly/2EQcN17

🏛 Why it Matters for Government: This was a great read leveraging research from ARK Invest regarding the anticipated economics of autonomous taxi revenues. ARK divides the autonomous taxi market into four types of providers: platform providers, lead generators, vehicle manufacturers, and owner/operators. The conclusion from their research is that Owner/Operators will receive the largest share of revenue per mile, yet this could be offset by the cost of ownership and maintenance. For government agencies, it’s important to follow the economic research of all autonomous technologies, because their rise will inevitably disrupt government revenues.

Read the full article on Medium