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1INNOVATION MANAGEMENT REPORT
By Larry Blue
How does a company grow its services revenue when the industry it inhabits has been declining because of the conversion to digital media? That was the challenge Bell and Howell met by asking, “What do we change? Which direction do we go? How shall we innovate?
In his Nov/Dec 2015 CIMS IMR article, then-Chief Technology Officer Brian Bowers related how he and his colleagues answered these questions by following the CIMS System laid out by Paul Mugge and Stephen Markham in their 2015 book, Traversing the Valley of Death: A practical guide for corporate innovation leaders.
In his article below, Bell and Howell Chief Operating Officer Larry Blue takes up where Bowers left off: from 2015’s first implementation of the CIMS process through 2017 when five new projects had grown revenues from zero to 10% of the corporate total.
The first stage of the CIMS System for Industrial Innovation (see illustration below) is where ideas are identified, quantified and turned into business opportunities; the second stage creates “the compelling case,” which includes actions like customer interviews to validate and verify assumptions about the market value of the candidate idea and then lead into developing a standard business case (and not a plan!)
July/August 2018
Corporate Experience
GROWING SERVICE BUSINESS AT BELL AND HOWELL—II
In This Issue
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CIMS INNOVATION MANAGEMENT REPORT
How Bell and HowellGrows Its Service Business
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News From theInternet of Value
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InnovationLit: The Future Computed,The AI Frontier, AI’s Impact On Innovation, Enterprise Risk Management, GenderEquality In STEM, Training PhD Students To Think,And More
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Acting EthicallyIn An AI World
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About CIMS 9
Matching Faculty Expertise With Industry Challenges
Since Our Last Issue: Innovation News YouMay Have Missed
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Bell and Howell transfers a compelling business case to a larger corporate team (Module 3 of the CIMS System for Industrial Innovation) only after landing the first customer/opportunity.
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We followed that process through those two stages but with some “tweaks” dictated by our internal rules and expectations. The first change to what we call “CIMS Lite” was to force quick decisions by limiting to 90 days the time we spent going from ideation through creating the compelling case. We aimed to define the idea in Week 1 or sooner; build the opportunity by Week 4; elaborate and evaluate by Week 10; and develop that compelling business case by Week 12.
We don’t want people to “boil the ocean” trying to define and identify a breakthrough idea, which is the purpose of the CIMS process, as opposed to incremental change. We came to the conclusion that breakthrough ideas should be relatively obvious after you get through the “elaborate and evaluate” stage 2A — that the answers to the questions, the feedback from potential customers, all of that, should drive you to a relatively quick decision. Hence our 90-day target.
Typically the people defining the idea are those with passion for the idea, the champions. Because they’ve already thought about it some, actually reducing those thoughts to a couple of pages is usually a fairly quick process. We want to basically flesh out those ideas and the interactions
Preventing Corporate Culture From Getting In the Way
Large organizations tend to avoid anything new because executive heads are down trying to execute against the plans they’ve put firmly in place. As a result, there’s built-in resistance to new product ideas and approaches that steal time and disrupt the normal order.
Here are four activities to counter those tendencies and foster innovation and entrepreneurship within a culture that doesn’t like change.
1. First and foremost, the executive team has to create an employee outreach and training program about how to be innovative and how the CIMS process can turn an idea into a potential business opportunity. You must be committed to innovation and you must be visible about it.
2. Management must provide the air cover to nurture and protect the embryonic projects because there are always parts of the organization that will insist it can’t be done differently, that the innovators have to follow company procedures for acquiring resources, bringing in vendors, and so forth. Those bureaucratic processes were put in place to institutionalize and protect the larger, established business units.
3. Sometimes you have to break rules in order to lift new ideas and innovative projects off the ground. Nurturing and protecting embryonic projects means that you have to do things differently— often sooner and faster—than what most large organizations are structured to do.
4. You must recognize and reward the thought leaders. Publicize promotions, opportunities for advancement, bonuses, and other means of recognition so that people understand you’re not just talking about innovation but putting your money where your mouth is.—L.B.
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“We don’t want people to ‘boil the ocean’ trying to define and identifya breakthrough idea.”
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with other parts of the business and the strategy by Week 4. Finally, we do a relatively light business case which is typically 5 to 10 pages looking at all of the critical aspects—competitive positioning, value proposition, et cetera.
The second thing we do is keep the team sizes small, typically less than four people through Stage 2. That’s because of what I call the white blood cells attacking the foreign object in the body; that happens when you get folks saying “we tried that before and it didn’t work,” or, “we can’t do that because our systems won’t allow us to do it that way,” and so on. There are always naysayers when you’re trying to start something new.
So rather than burden the champion and the team with those naysayers, we keep moving these small teams forward through the business case until we get our first customer, which really commits the organization to that business. Only after landing that first customer opportunity do we introduce it to the broader organization (Module 3 in the CIMS System).
We’ve found that’s the best way to provide the “air cover” needed for embryonic businesses to grow to the point where they can withstand the “driving rain and high winds” that buffet any new business started inside a large, older organization.
Agile Development
We also apply the agile development practices of sprints and scrums during the discovery process in Stages 1B and 2A. The whole idea is to tackle a difficult problem first and find solutions to that problem before moving on to something else.
In the product-development engineering world you can do a lot of the easy work first but if you delay tackling the hard stuff and the unknowns you could end up having to go back and redo all of the old easy stuff. That’s why we applied those same development concepts to building our business case by attacking the unknowns first and allowing no more than two weeks to resolve them.
That helps us weed out the weaker ideas early on because if you can’t solve the unknowns—if you can’t gather the information or identify the right customer or market segment—then you’re likely to have a difficult time finding a breakthrough innovation.
Meeting Weekly
Weekly meetings with the sponsors, champions and executive management is an important part of our CIMS Lite. I sat in on every one of those for the first wave of our CIMS projects to make sure the team was making progress following the process and sticking to the timetables we had set. This is where Brian Bowers was a big help, acting as the experienced process owner for CIMS and advising the teams on the steps they needed to take.
Executive management then made sure that when the team ran into a problem they lacked the right skill for, Brian and I were able to find answers from operations, finance or somewhere else in Bell and Howell.
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“Tackle a difficult problem first and find solutions to that before moving on to something else.”
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First Customers
After we came up with a business case and the customer opportunity, we kept the team small and started to involve our business development and sales people to go out with the defined value proposition and find that first customer. Between 2015 and 2017 we launched the five successful projects described below.
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“First and foremostwe have to find people who are passionate.”
CIMS Lite Projects
1. Our first project, which launched in 2015, was a system configuration backup solution for our sortation equipment. The proposed solution saves the setup configurations of the multiple processors in the sorting machine, enabling recovery from a processor or equipment error. Rebooting prior to this solution would have taken hours.
This was more incremental than breakthrough but an important first step. We’ve done about $1 million in revenue to date in that project. We subsequently folded it into the larger Bell and Howell organization so it is now one of our service group’s product offerings.
2. Raptor was a breakthrough labeler product that created a different, more efficient, way of printing a label for packages. Raptor can label different-sized boxes on a conveyor belt at three to five times faster than anybody else in the industry because we invented a way to “print on the fly.” It’s for fulfillment centers that need different types of labels printed quickly on the boxes.
Raptor sales in 2016 were over $400,000, and the future value of this product improved the value we gained from the sale of our sorting business in 2017.
3. We had been selling an “enveloper” machine for the past 10 years with little success and used the CIMS process to develop a more effective sales strategy. Although the analysis resulting from the process identified the need for a lower- cost solution, we decided to discontinue the effort after learning some useful lessons.
4. New market applications for our mail tracking technology was another area that the company had talked about for several years, convinced this technology clearly has applicability beyond mail. We decided that if we truly believed this, we would use the CIMS process to prove it or not. This became our Track and Trace opportunity, which we closed on with Colgate Palmolive in 2016 for $1.3 million. It met FDA requirements that drug manufacturers have their products serialized by Nov. 2018.
5. Smart Lockers are Internet- and wireless- enabled versions of your old school locker that retailers are using in their e-commerce strategies to encourage “buy online, pick up in store” customer transactions. This was a completely green- field opportunity that fit our strategy very well because in order to launch these smart lockers you needed the ability to do installations and maintenance and support nationwide. We won our first account in July 2016 and as this article was written we had installed our first 100 of these units at a large retailer.
These CIMS Lite businesses accounted for 10 percent of our 2017 revenues and are projected to provide 39 percent of our 2018 revenue. Clearly these new business opportunities have had a significant impact on the product portfolio and the growth opportunities for Bell & Howell.—L.B
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CORPORATE EXPERIENCE FROM PG 4
CIMS is a Graduated NationalScience Foundation industry/university cooperative researchprogram supported by thefollowing organizations: AirProducts & Chemicals, Inc., TheAmerican Coatings Association,BASF Corp., Bell & Howell,BioResource International,Eastman Chemical, I2M, LLC,Inivata, Kelly Services, Inc., National Association of Broadcasters, Pentair Aquatic Ecosystems, Syngenta,Toshiba Global CommerceSolutions, NC State UniversityPoole College of Management,Kenan Institute for Engineering,Technology & Science, and theIndustrial Research Institute.
CIMS is located at NC State University, 2801 Founders Drive, Campus Box 7229, Raleigh, NC 27695-7229.
Tel: (919) 513-0166Fax: (919) 515-6943 Website: http://cims.ncsu.edu
PAUL C. MUGGEEXECUTIVE DIRECTOR
ALDEN S. BEAN EXECUTIVE DIRECTOR, EMERITUS MICHELLE L. GRAINGER MANAGING DIRECTOR STEPHEN K. MARKHAM RESEARCH FELLOW FRED RENKCIMS INDUSTRIAL [email protected] TIM MICHAELISCIMS PhD [email protected]
RICHARD KOURICIMS CHIEF [email protected]
MICHAEL F. WOLFFEDITOR
“Finally, you need an internal process owner and evangelist as your innovation leader.”
Keys to Success
Looking back on the lessons we’ve learned from those five projects, I find the following three “must haves.”
1. Innovation champions who possess both passion and persistence. Without those you don’t overcome the inertia of the larger organization and the project will die. We try to involve people who have some experience with product management, marketing, finance, or manufacturing; but first and foremost we have to find people who are passionate.
2. “Air cover” and patience from the executive sponsor. Breakthrough ideas stress an organization that already has business goals and values. So if you have a breakthrough idea like our Smart Lockers, for example, it’s competing for resources with large established organizations that already have budgets and revenue targets, and can’t be bothered with this nuisance business that’s just starting up. You have to protect that business to move it beyond its embryonic state.
3. Finally, you need an internal process owner and evangelist as your innovation leader. We had that in Brian Bowers. He was the muse, advisor and subject matter expert who the innovation champion could go to for guidance, learning and assistance in working through the rigorous steps of the process.
Because the process requires commitment to getting it done, you need people with passion being directed by people who understand the process so the passionate people don’t get bogged down in bureaucracy but also don’t skip steps.
Going Forward
As we began to drive a second wave of new ideas by re-launching CIMS Lite in 2018 we recognized that we could do better at building the opportunity (Stage 1B). We also want to do more thorough market analysis in order to identify more potential markets for our new ideas. We also need to communicate our successes better internally in order to stimulate more new ideas. And then we need to assign and train new process owners.
Healthy companies need 30 to 40 percent of their revenues coming from new ideas every 3 to 5 years. That’s the value of innovation, because you either innovate or you die and we need to continue to innovate.
Larry Blue; COO, Bell and Howell LLC, Durham, NC; [email protected]
“Healthy companies need 30-40% of their revenuescoming from new ideas every 3 to 5 years.”
6INNOVATION MANAGEMENT REPORT
By Nena M. Ellis
Since launching its interactive platform in Fall of 2016, The Pennsylvania State University has seen strong participation from researchers, positive feedback from participants, and new opportunities for partnership with industry.
Penn State’s Innovation Gateway is an interactive online platform created by the university’s Office of Industrial Partnerships (OIP) to increase collaboration between University researchers and industry.
Companies that work with OIP can use the online platform to connect with Penn State researchers and research teams who can help meet industry challenges. The collaborations increase commercialization opportunities for Penn State research and encourage research teams to use their skills and discoveries in applications that can solve real-world business problems.
Nearly two years after the 2016 launch, the program has seen strong initial results. “Innovation Gateway has already proven to be an incredible resource to engage industry partners and to enable us to reach all areas of the university quickly,” says Don Mothersbaugh, associate director for the Office of Industrial Partnerships. “The tool has been well-received by both faculty and corporate partners.”
10 Companies, 71 Research Proposals
More than 10 companies posted Innovation challenges in the tool’s pilot year, including three Fortune 500 companies. In response, researchers from numerous departments and academic disciplines submitted 71 research proposals to address those challenges.
Using Innovation Gateway, companies work with OIP to post specific details of a business challenge or technological need. They can also post a simple request for more information (RFI) or a request to partner (RFP) to open the door for collaborative work.
The requests are distributed to some 5,000 Penn State researchers. Interested faculty, staff or postgraduate teams can then respond with information about their research expertise, ideas and solutions using a simple standardized format within the tool.
After reviewing submissions, a corporate partner can choose to meet with research teams, begin to develop longer-term partnerships, or move immediately to fund research. The tool enables industry to access research expertise in the university they might never have known about otherwise.
Challenges have been submitted by industry leaders in diverse industries—food and beverage, cosmetics, software, automotive, chemical manufacturing, and materials. These challenges may be specific to the company’s business needs, like a request to remove a specific material
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Innovation Management
PENN STATE’S INNOVATION GATEWAY MATCHES FACULTY EXPERTISE WITH INDUSTRY CHALLENGES
“More than 10 companies including three Fortune 500 posted innovation challenges in the tool’s pilot year.”
7INNOVATION MANAGEMENT REPORT
from a manufacturing process, or high-level “blue ocean” challenges, like a request to reduce a company’s overall carbon footprint, that allow Penn State research teams to think broadly about opportunities.
Volvo’s Challenges
One of the first companies to complete a research challenge through Innovation Gateway was The Volvo Group, which posted two separate challenges related to energy efficiency and advanced manufacturing in the Fall of 2016. More than 20 Penn State researchers responded, with submissions from departments including mechanical engineering, materials science and engineering, the Applied Research Laboratory, and others.
Stephen Lynch from Penn State’s Department of Mechanical and Nuclear Engineering submitted the
final selected research project, for a 9-month study titled “Optimized Lightweight Diesel Engine Waste Recovery Heat Exchangers via Additive Manufacturing.” The proposal was submitted in response to Volvo’s challenge in the category of energy- efficient vehicle innovation.
Although Volvo has previously worked with a number of Penn State research teams through its Academic Preferred Partner program, 85% of the faculty who participated in this challenge, or 17 researchers, were previously unknown to the manufacturer, opening the door to new expertise and partnerships.
Bringing New Ideas to the Table
Researchers from any Penn State department at any campus can make submissions to a given challenge. “That openness broadens the pool of potential solutions and brings new ideas to the table,” said Mothersbaugh. “It really helps companies to think outside the box.”
He cited the example of a unique research response submitted to Volvo: A liberal-arts researcher suggested a potential human behavioral solution to the challenge where others had approached the problem from a technical angle.
Tak-Sing Wong, Assistant Professor of Mechanical Engineering and Biomedical Engineering, participated in an Innovation Gateway challenge for the first time this past Fall. His research team submitted a proposal to, and was selected to work with, a global cosmetics company to refine cosmetic products using their expertise in surface science and engineering.
Prof. Wong gave the process high marks for its simplicity and efficiency. “Our research group benefited tremendously from the platform,” he said. “Not only was it an efficient way to identify key business problems to solve, but as part of the process, we were able to meet face-to-face with our potential partners, allowing us to interact with them directly.”
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“Volvo Group was one of the first companies to complete a research challenge through Innovation Gateway.”
The Innovation Gateway platform is an open innovation tool that allows Penn State researchers to collaborate with industry.
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In addition, Wong notes that the Innovation Gateway platform is particularly valuable for junior faculty members who may not have the same connections to outside industry partners that more established faculty have cultivated. This is the first time he has worked in an industry research collaboration.
Connecting Faculty and Industry
While digital platforms exist for government-funded research grants, Innovation Gateway is the first to connect Penn State researchers with industry. Jeff Fortin, associate vice president for research at Penn State and director of the Office of Industrial Partnerships (OIP), says that the tool helps to bolster their overall, ongoing support for faculty-industry connections.
“Our goal is to take the burden off of faculty and help to facilitate these partnerships,” says Fortin.
Leaders of the program hope to add collaboration features to the platform so that faculty, staff or post-graduate students can work together to review and collaborate on a given proposal.
“Penn State’s land grant mission is to educate, research, and conduct outreach beyond our walls,” says Fortin. “This program truly captures all three. We’re working with partner organizations, and we’re engaging our faculty and students to grow real expertise while solving real-world problems.”
Innovation Gateway is one piece of the much larger Invent Penn State initiative, a $30 million dollar commitment by Penn State President Eric Barron announced in 2015 to leverage university research and resources to support innovation and entrepreneurship. Invent Penn State has resulted in many new programs, tools, incentives, resources and partnerships at the university—all designed to drive job creation, economic development and student career success.
Nena M. EllisDirector of Marketing and Communications, Invent Penn State, [email protected]
By Patrick Lin
“It‘s difficult to think of a real-world example where ethics may be ignored because the benefits are so compelling,” write Patrick Lin and co-editors Keith Abney and Ryan Jenkins in their preface to Robot Ethics 2.0: From Autonomous Cars to Artificial Intelligence (Oxford University Press, Sept. 2017).
Prof. Lin directs the Ethics+ Emerging Science Group at California Polytechnic State University, where his co-editors also teach. In
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“Innovation Gateway is one piece of the much larger Invent Penn State initiative to support innovation and entrepreneurship.”
Innovation Advance
AUTONOMY AND ETHICS IN AN AI WORLD
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October 2017, he was a plenary speaker at the National Academy of Engineering annual meeting, which addressed the ethical questions and abundant opportunities provided by the emergence of autonomous technologies. His presentation, “Autonomy and Ethics,” is condensed and edited here. The original with images can be found at https://www.nae.edu/Events/AnnualMeetings/AnnualMeeting2017.aspx
Let’s start with a working definition of Artificial Intelligence. It’s not this magical, mystical thing, but just a complex computer program that’s designed to automate decisions and actions. And it does this with the appearance of intelligence.
You can make a comparison between AI and bureaucracy. Just like AI, bureaucracy defines and automates certain decisions. I believe this foreshadows an ethical problem for AI (and bureaucracy), which is that if you’re not careful you can slip in systemic risk and other vulnerabilities.
Before discussing this risk, consider that AI is reaching all of our world’s major domains.
Six Domains of AI
On land, we have AI in our everyday devices, from smart phones in your pockets and virtual assistants on the kitchen table to smart thermostats, connected refrigerators, self-driving cars, factory and mall security robots, and more.
In the air, airplanes are already autonomous, military drones are really semi-autonomous, while some cruise missiles are fully autonomous.
On the sea, any place where you find a human being is a market for AI, just like for the other domains. We’re already seeing autonomous surface ships and submarines, for example.
In outer space, researchers are working on robot astronauts, and we find AI in Mars rovers and satellites, and other systems.
Then there’s inner space—the space inside our bodies—where AI is being used for medical diagnosis as well as connecting to us more intimately; for instance, in augmented reality flight helmets and the “neural lace” that Elon Musk is planning to make, which means AI can shape the way we view the world.
Finally, there’s cyber space. AI is in expert systems for criminal sentencing, hiring and banking. Medicine and science are using it to discover scientific principles that not even humans have discovered.
Super-Automated Decision-Making
All these different forms of AI present different kinds of issues, from job displacement to unclear responsibility, privacy, psychological effects, and a possible AI arms race. But I’ll focus here on the core issue of proper decision-making. If AI is really about super-automation of decisions, it’s fundamental to ask whether we are doing that right.
There are three kinds of decisions: decisions that are right, decisions that
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ABOUT CIMSThe Center for Innovation Management Studies (CIMS) represents a one-of-a-kind convergence of academia and industry.
Its mission is to “create, synthesize and disseminate industry-relevant information on innovation management, and to develop current and future generations of innovation management researchers and industry practitioners.”
CIMS is dedicated to fostering a collaborative environment among scholars, researchers and business executives.
To achieve success, CIMS first listens to companies describe their toughest business challenges. Then it uses an array of proven diagnostic tools to locate and better define the problem and form a team of research faculty, CIMS Fellows, and students to work with the company to solve their problem.
CIMS was created in 1984 at Lehigh University to fund academic research on topics chosen by industrial R&D managers. Its goal was to better understand the technological innovation process and how it could be managed more effectively.
Today, 34 years later, CIMS is housed in the Poole College of Management at NC State University, located in the vibrant, technology-rich Research Triangle Park region of North Carolina. It has sponsored thousands of hours of research, held scores of workshops and conferences, published hundreds of papers, and improved the balance sheets of dozens of companies.
Membership informationand complete list of
benefits/services available from CIMS office at
(919) 513-0166; [email protected]
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are wrong, and a weird gray space of decisions that are neither wrong nor right. These are decisions that require a judgment call, or an ethics call. To give AI the best chance possible, I shall assume that it works as designed, that none of the sensors are broken, and that the system has not been hacked.
Even if we built an AI system right—if we built it to spec—we should ask whether we built the right thing. Did we build what was actually needed? With that in mind, I’ll ignore the decisions that are right and look first at the wrong ones.
Wrong Decisions
One way AI can go wrong is by exhibiting emergent behavior—behavior we didn’t expect and that we don’t want. We’ve already seen this with stock market flash crashes where autonomous financial trading bots, working against each other at digital speeds, crash the stock market and cause real losses.
This actually happens more often than you might think; it happens because AI is incredibly complex, and with complexity you often get unpredictability. When you have two autonomous systems meeting each other for the first time, that compounds the unpredictability.
Several years ago, for instance, Amazon had this weird case where a couple of pricing bots were basically having an auction between themselves over a used textbook about flies. They drove up its price to $23 million!
Other worries include what happens if our robot army meets an adversary’s robot army for the first time? We can’t predict what the effects are, and our adversary is unlikely to loan us their robot to make sure it’s interoperable with ours.
There are similar concerns with self-driving cars. Will cars from different manufacturers be able to negotiate around each other and interoperate without an industry standard, for instance?
Gaming the AI
Another way an AI system can make a wrong decision is if you game it by, for example, introducing an adversarial example. I’m talking here about learning AI: neural nets that require tons of examples or training data to identify a pattern and figure out things for themselves.
In one 2014 exercise, Google researchers created an AI system that could learn to identify pandas, cats and other animals by analyzing millions of images. In this case, it identified the panda image with a 60-degree confidence rate.
Then the researchers slipped a tiny bit of imperceptible, pixilated noise into that image. As a result, the AI came up with a composite picture that it erroneously believed to be a monkey with 99 percent confidence! That’s one way we can trick learning AI—we cannot always predict what it’s going learn.
We can see how this translates into a real-world risk. For instance, the
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“If AI is really about super-automation of decisions, it’s fundamental to ask whether we are doing that right.”
“One way AI can go wrong is by exhibiting behavior we didn’t expect and that we don’t want.”
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camera from a self-driving car might be filming its surroundings but if you introduce the right adversarial example, the people can become invisible to the computer.
Recently researchers have shown that you don’t even need to hack into the system. All you really need are little bits of tape strategically placed on a sign, manipulating it just a tiny bit. Now, all of a sudden, this bright red stop sign appears to the car’s computer like a 45- mile- an- hour speed limit sign. Computer vision is still imperfect! There’s still a lot of work that needs to be done.
Algorithms Crystallize Bias
Even if you’re not gaming AI it can go wrong by producing biased answers. This applies mostly to learning algorithms that rely on lots of data. If you start with bad data, you have the garbage-in, garbage-out problem. A famous example is a man searching for a job online who’s more likely to be shown job ads for CEO positions than if he were a woman. That’s an accurate reflection of the data, but the data may be a broken reflection of a society where historically CEOs were mostly white men, given more overt sexism and racism.
As my Cal Poly colleague Ryan Jenkins puts it, algorithms tend to crystallize bias. So, once it’s in an algorithm, further thinking tends to stop. The data scientist Cathy O’Neil, who wrote this excellent book, Weapons of Math Destruction, puts it nicely; she said algorithms are opinions embedded in code. That means that data and algorithms aren’t as objective as you might think they are.
Decisions Neither Wrong Nor Right
Let’s look now at this subtler category of decisions that are not wrong but also not right. Imagine you’re in a robot car driving on your local freeway. You’re in the middle lane and for whatever reason you’ve got to swerve. Do you swerve to the right and hit that small car or do you swerve left and hit this larger car? There are reasons to go either way. If you’re worried about your passengers, you should swerve left and crash into the larger object and protect those passengers better. On the other hand, if you’re worried about your own life, then you should crush that smaller vehicle.
Either way is reasonable, but once you make that decision, you are systematically discriminating against a particular class of vehicles through no fault of their own, other than the owners couldn’t afford larger cars or they have large families. It’s important to remember that programmed decisions are premeditated decisions, and law and ethics treat these two differently. This is the difference between an innocent accident and potentially premeditated homicide.
This doesn’t only apply to weird crash scenarios. There are ethical dilemmas in the everyday decisions a self-driving car has to make, as my colleague Noah Goodall in Virginia also points out. For instance, imagine you’re going down a narrow road and encounter a group of five people on one side and a single person on the other. Where do you position the car? Do you weigh all six lives equally and let it drive straight down the middle, or do you give the group more space because you decide the five people are worth more than one?
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“Even if you’re not gaming AI it can go wrong by producing biased answers.”
“There are ethical dilemmas in the everyday decisions a self-driving car has to make.”
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There are many such scenarios, even today with navigation apps that choose a route for you; they tend to default to the fastest path, no matter the risk. These scenarios all raise questions about how we value different lives and what tradeoffs we’re willing to make. There’s no obviously right way but you should recognize that whatever decision you or your robot make involves transferring risk among one or more parties, and no one asked you to do that.
These ethical issues also come up with military robotics. The laws of armed conflict have many conditions that require judgment calls, and there’s a huge body of literature on that.
Superhero Ethics
It’s often helpful to connect new, unfamiliar things—like AI ethics—to the more familiar. I’d suggest that we can think about technology as a super power. Drones, for instance, are giving us the ability to fly. With drones, you could see into the windows of a 38-floor apartment building just like Superman could. Surveillance cameras and tiny sensors give us super senses—super vision, super hearing. AI combined with big data gives us omniscience!
So Facebook might know a lot more about your family history than you even know. A few years ago, Target.com reportedly learned that a daughter was pregnant before her parents even knew. That’s omniscience.
Bionic exoskeletons give us super strength. Biotechnology has given us super-metabolism; the military is working on soldiers who don’t need to eat or sleep. Nanotechnology has given us meta-materials, some of which act like invisibility cloaks right out of Harry Potter. Computer brain interfaces are essentially giving us the power of telepathy. CRISPR and gene editing let us create mutants.
These are literally super powers that jump off the pages of comic books. That means we can think of technology ethics as superhero ethics. So, think of technology ethics as asking the question: What happens when we get super powers? How do super powers change ethics? How do they change our institutions, like privacy and education? How do they change our norms? As the saying goes, great powers come with great responsibility. Today new powers come with new responsibilities.
Imagine we’re in Metropolis where Luther has planted a bomb. You’re not obligated to pick up the bomb and throw it into outer space. It makes no sense to say you have a responsibility to do something you physically cannot do. But Superman has this responsibility. He can do it. And arguably, he should do it. So, we have to think about the ways that technology is changing us—changing our obligations and responsibilities.
We’re all stakeholders in this technology-driven world. You might not be interested in robot cars, but robot cars might be interested in you as they drive alongside you and your friends and family. I like to close with this quote from British scientist Sir Martin Rees, in The Guardian: “Scientists surely have a special responsibility. It’s their ideas that form the basis of new technology. They should not be indifferent to the fruits of their ideas.”
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TECHNOLOGY= SUPERPOWERS
• Ability to fly • Super senses • Omniscience • Super strength • Super metabolism • Invisibility • Telepathy • Creating mutants • And more
“Think of technology ethics as asking, What happens when we get super powers? How do super powers change ethics? How do they change our norms?”
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When law and policy concerning a new technology are unclear—our driving laws largely don’t contemplate an AI driver, for instance—it’s often helpful to go back to first principles. Go back to ethics as your moral North Star, your moral compass, to help point the way to sound law and policy.
Patrick Lin; [email protected]
More related reading from Cal Poly’s Ethics + Emerging Sciences Group at http://ethics.calpoly.edu/robots.htm
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“Go back to ethics as your moral North Star, your moral compass, to help point the way to sound law and policy.”
Streamlining the Insurance Value Chain
First commercial blockchain product for proof of insurance is being developed by Marsh, a global insurance broker, and its collaborators IBM, the Association for Cooperative Operations Research and Development (*ACORD) and Marsh client ISN. ACORD is the global standards-setting body for the insurance and related financial services industries. ISN, a global contractor and supplier information manager, plans to pilot the product when it goes into production later in 2018.
“By using blockchain technology,” says the announcement, “Marsh is fundamentally transforming the certificate of insurance process from complicated and manual to streamlined and transparent, allowing clients to speed up necessary business functions such as hiring contractors and transferring risk while increasing coverage certainty.”
“This is an ideal example of how blockchain can be used on a much broader scale to drive real business results,” said Sandip Patel, IBM general manager for the insurance industry.
Waking Up the Oil Patch
“The oil majors are waking up to blockchain possibilities,” claims Meredith Taylor in “Why The Next Oil Boom Will Be Fueled By Blockchain,” oilprice.com, Feb 21, 2018. Taylor sees blockchain advancing the World Economic Forum’s 2017 picture of a digital transformation having already swept across the energy industry. Her report includes:
• Canada’s Petrobloq, “the first Blockchain-based platform developed exclusively for the supply chain needs of the Oil & Gas sector,” aims to reshape the industry from drilling to petroleum-based end- product by its ability “to track, monitor, and account for every drop of petroleum on a transparent, immutable, and secure blockchain.”
• British Petroleum began experimenting with a blockchain-based oil trading platform in Oct. 2017. Its goal: “implementing ‘practical and ethical’ uses of the technology.”
• Royal Dutch Shell is leading a blockchain movement with BP to launch a platform by the end of 2018 that will “revolutionize the way oil and gas are sold.”
Blockchain Update
ON THE INTERNET OF VALUE
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Blockchain Labs for Maritime Risk and Safety
Lloyd’s Register Foundation and Blockchain Labs for Open Collaboration (BLOC) are partnering to form Maritime Blockchain Labs (MBL) to explore blockchain technology for maritime risk and safety.
The Foundation is a United Kingdom charity established in 2012 to protect the safety of life and property (http://www.ir.org). According to its March 22 announcement, the partnership will fund MBL over the next 18 months to pursue three demonstration projects “focused on aspects of risk and safety where distributed systems can enable breakthrough solutions.”
Another MBL objective is “to establish an ecosystem within the sector to foster innovation and collaboration between blockchain practitioners and industry actors, share knowledge and best practices, collectively define problems, and shape solutions that are open and interoperable.”
Gary Pogson, author of the Foundation and the Alan Turing Institute’s Insight Report on distributed ledger technologies, concludes that “distributed ledger and blockchain technologies have a potentially wide range of applications related to engineered systems and supply chains, particularly in helping to address safety challenges of sectors such as maritime.”
Making Shipping ‘Smarter’
Retail giant Walmart’s application to patent its blockchain-based “Smart Package” system was released by the U.S. Patent and Trademark Office on March 1, reports Fintech Finance( fintech.finance).
Fintech explains that the application states that a blockchain component encrypted into the device will have “key addresses along the chain of [the package’s] custody, including hashing with a seller private key address, a courier private key address and a buyer private key address.”
The patent builds on a filing Walmart submitted in 2017 for a blockchain-based drone package delivery tracking system.
Boosting Manufacturing
A public, open-source network using blockchains to share verifiable manufacturing data has been proposed by researchers at North Carolina State University.
“Our approach, called FabRec, would allow companies to automatically report about their manufacturing activities: which machines are being used, what materials they are working with, raw material inventory levels, whether the work is being completed on time, and so on,” says Atin Angrish, a Ph.D. student at NC State and co- author of “A Case Study for Blockchain in Manufacturing: ‘FabRec’: A Prototype for Peer-to-Peer Network of Manufacturing Nodes.”
The paper was presented at the SME North American Manufacturing Research Conference, held in Texas in June (arix.org).
“A public network like the one we’re proposing would help potential clients find manufacturers with relevant expertise and equipment in an efficient way,” says corresponding author Binil Starly, an associate professor in NC State’s Industrial & Systems Engineering department.
Transitioning to Industry 4.0
Blockchain tools like smart contracts and decentralized autonomous organizations can aid the transition to Industry 4.0, says a report from market advisors ABI Research (abiresearch.com).
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The April 2018 whitepaper by ABI’s Michela Menting—“How Blockchain is Impacting Industrial Manufacturing and Supply Chain Logistics ”—asserts “The use of decentralized ledger technologies such as blockchain can provide transparency on product movement, automate numerous logistical tasks, optimize workflows and reduce friction throughout the value chain.”
Along with several blockchain use cases, the paper discusses the industrial drivers, current and upcoming industrial issues, and the barriers and challenges to blockchain adoption. It can be ordered at https://www.abiresearch.com/pages/how-blockchain-impacting-manufacturing.
InnovationLit
THE FUTURE COMPUTED, THE AI FRONTIER, AI’S IMPACT ON INNOVATION, ENTERPRISE RISK MANAGEMENT, GENDER EQUALITY IN STEM, TRAINING PHD STUDENT TO THINK, AND MORE
THE FUTURE COMPUTED: ARTIFICIAL INTELLIGENCE AND ITS ROLE IN SOCIETY; Microsoft Corporation with a foreword by Brad Smith and Harry Shum; Microsoft, Redmond Washington, 2018.
“Skilling-up for an AI-powered world involves more than science, technology, engineering and math….If AI is to reach its potential in serving humans, then every engineer will need to learn more about the liberal arts and every liberal arts major will need to learn more about engineering.”
So write Microsoft’s president/chief legal officer and the executive VP of Microsoft’s Artificial Intelligence and Research group in their foreword to this Microsoft book with 40 contributors.
Smith and Shum also ask rhetorically whether computer programmers and researchers will be required to study ethics. “We believe that’s a safe bet,” they say. “Could we see a Hippocratic Oath for coders like we have for doctors? That could make sense.”
Their foreword follows with four chapters—“The Future of Artificial Intelligence,” “Principles, Policies and Laws for the Responsible Use of AI,” “AI and the Future of Jobs and Work”—and a concluding “AI Amplifying Human Ingenuity.”
Six core principles are presented that Microsoft believes “should provide the foundation for the development and deployment of AI-powered solutions that will put humans at the center: fairness, reliability, privacy and security, inclusiveness, transparency, and accountability.”
Smith and Shum add: “A continuing collaboration between government, business, civil society, and academic researchers will be essential to shape the development and deployment of human-centered AI to be trustworthy. Ongoing dialogues among these communities will help to identify and prioritize issues of societal importance, enable further research and development of solutions and sharing of best practices as new issues emerge, and, where appropriate, shape policy that can more readily adapt to these rapidly evolving technologies.
“Could we see a Hippocratic Oath for coders like we have for doctors? That could make sense.”
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The book examines six areas Microsoft considers critical for enabling people “to thrive in today’s economy and prepare for tomorrow’s”:
• Giving every young person the opportunity to study computer science.
• Helping workers gain relevant skills for a changing workplace.
• Creating a skills-based marketplace that helps companies find qualified employees and enables workers to find jobs.
• Providing legal certainty for employers and workers so that they understand their rights and obligations.
• Developing industry standards to protect on-demand workers with fair pay and treatment.
• Ensuring that benefits move with workers, and reforming social safety nets to provide adequate coverage for workers and a sustainable contribution structure for businesses.
THE FUTURE COMPUTED concludes with this admonition: “A human-centered approach can only be realized if researchers, policymakers, and leaders from government, business and civil society come together to develop a shared ethical framework for artificial intelligence. This in turn will help foster responsible development of AI systems that will engender trust. As we move forward, we look forward to working with people in all walks of life and every sector to develop and share best practices for building a foundation for human-centered AI that is trusted by all.”
NOTES FROM THE AI FRONTIER: APPLICATIONS AND VALUE OF DEEP LEARNING; Michael Chui et al; McKinsey Global Institute, April 2018; mckinsey.com
This discussion paper analyzes more than 400 use cases across 19 industries and nine business functions in order to assess ”the broad use and significant economic potential of advanced AI techniques.”
Drawing on McKinsey Global Institute research and the applied experience with AI of McKinsey Analytics, they discuss a number of insights from the use cases, including:
• “Deep learning’s capacity to analyze very large amounts of high dimensional data can take existing preventive maintenance systems to a new level.
• “AI-driven logistics optimization can reduce costs through real-time forecasts and behavioral coaching.
• “AI can be a valuable tool for customer service management and personalization challenges.
• “Two-thirds of the opportunities to use AI are in improving the performance of existing analytics use cases.
• “Data requirements for deep learning are substantially greater than for other analytics.
• “Realizing AI’s full potential requires a diverse range of data types including images, video, and audio.”
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“AI’s impact is likely to be most substantial in marketing, sales, supply-chain management, and manufacturing.”
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Next, the authors discuss the potential value of AI techniques, which they estimate could create between $3.5 trillion and $5.8 trillion in value annually across the nine business functions in 19 industries. They see AI’s impact likely to be most substantial in marketing, sales, supply-chain management, and manufacturing.
Their concluding section, “The road to impact and value,” examines AI’s limitations; organizational challenges around technology, processes and people; AI’s “elusive” business case; and implications for stakeholders.
Their final word: “Given the scale of the beneficial impact on business the economy and society, the goal should not be to constrain the adoption and application of AI, but rather to encourage its beneficial and safe use.”
“THE IMPACT OF ARTIFICIAL INTELLIGENCE ON INNOVATION”; Iain M. Cockburn, Rebecca Henderson and Scott Stern; National Bureau of Economic Research Working Paper 24449, March 2018, http://www.nber.org/papers/w24449
Artificial intelligence could potentially serve as “a new general-purpose ‘method of invention’ that can reshape the nature of the innovation process and the organization of R&D,” predict these management professors from Boston U. (Cockburn), Harvard Business School (Henderson) and Stern (MIT).
Identifying machine learning as “the invention of a method of invention,” they foresee consequences for both the economy and society at large as profound as those from artificial intelligence itself.
Their essay begins with the potential impact of AI advances on innovation and the role that policy and institutions might play. Then, in Section II, they examine how a research tool like deep learning applied to R&D problems can create “a new ‘playbook’ for innovation itself.”
Section III contrasts the roles likely to be played by the AI “trajectories” of robotics, symbolic systems and deep learning. They explain why they “see machine learning as the ‘invention of a method of invention’ whose application depends, in each case, on having access not just to the underlying algorithms but also to large, granular datasets on physical and social behavior.”
They conclude that “the prospect of a change in the innovation process raises key issues for a range of policy and management areas, ranging from how to evaluate this new type of science to the potential for prediction methods to induce new barriers to entry across a wide range of industries. Proactive analysis of the appropriate private and public policy responses towards these breakthroughs seems like an extremely promising area for future research.”
2018 THE STATE OF RISK OVERSIGHT: AN OVERVIEW OF ENTERPRISE RISK MANAGEMENT PRACTICES, 9TH EDITION; Mark S. Beasley, Bruce C. Branson, Bonnie V. Hancock; Enterprise Risk Management Initiative, North Carolina State University Poole College of Management (www.erm.ncsu.edu), March 2018.
Although more U.S. organizations are adopting enterprise-wide risk management, 69% lack such processes despite growing corporate risks.
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“A research tool like deep learning applied to R&D problems can create a new ‘playbook’ for innovation itself.”
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That’s the finding of a survey of 474 U.S. CFOs and senior finance leaders on how they are managing potential risks by strengthening their organization’s processes for the identification, assessment, management, and monitoring of risks—a concept known as ERM.
According to the report from NC State’s Enterprise Risk Management Initiative and the American Institute of CPAs, ERM practices in U.S. organizations remain relatively immature. Only 22% of the finance leaders described the maturity of their organization’s overall risk management oversight as “mature” or “robust.”
Among other study findings:
• Management wants a greater focus on risk.
• There is a disconnect between risk and strategy.
• Demand for Chief Risk Officers is growing.
• Risk management is not being considered for incentive compensation
• Competing priorities, insufficient resources, doubts about value, and other barriers limit progress in managing risk.
“Senior executives and boards of directors are realizing increasingly that the speed of change and the level of uncertainty in the global business environment is outpacing the ability of their organization’s traditional approach to managing risks,” said Mark Beasley, Deloitte Professor of Enterprise Risk Management and director of NC State’s ERM Initiative. “While many are increasing the robustness of their processes for identifying, assessing, and managing emerging risks that may ultimately impact their core business model and strategic objectives, a number of organizations may not discover that need until they face a major risk event.”
“The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education”; Gijsbert Stoet and David C. Geary; Psychological Science Feb 14, 2018, https://doi.org/10.1177/0956797617741719
Using an international database on adolescent achievement in science, mathematics and reading (472,242 students in 67 nations or regions) psychologists Gijsbert Stoet of Leeds Beckett University (UK) and David Geary, U. of Missouri, found “that girls performed similarly to or better than boys in science in two of every three countries; in nearly all countries, more girls appeared capable of college-level STEM studythan had enrolled.”
However, women obtained fewer college degrees in STEM disciplinesthan men in all assessed nations. And paradoxically, “countries with lower levels of gender equality had relatively more women among STEM graduates than did more gender-equal countries.”
Their analysis also suggests “that the percentage of girls who would likely be successful and enjoy further STEM study was considerably higher than the percentage of women graduating in STEM fields, implying that there is a loss of female STEM capacity between secondary and tertiary education.”
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“Only 22% of the finance leaders described the maturity of their organization’s overall risk management oversight as
“mature” or “robust.”
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They conclude that “achieving the goal of parity in STEM fields will take more than improving girls’ science education and raising overall gender equality. The generally overlooked issue of intra-individual differences in academic competencies and the accompanying influence on one’s expectancies of the value of pursuing one type of career versus another need to be incorporated into approaches for encouraging more women to enter the STEM pipeline. In particular, high-achieving girls whose personal academic strength is science or mathematics might be especially responsive to STEM-related interventions.”
“Train PhD students to be thinkers not just specialists”; Gundula Bosch; nature.com Feb. 14, 2018.
“Most PhD curricula are unlikely to nurture the big thinkers and creative problem-solvers that society needs,” asserts the director of the R3 Graduate Science Initiative at Johns Hopkins University School of Public Health. Gundula Bosch believes that students need to recognize how errors occur by evaluating case studies from flawed real research.
“Above all, students must be shown the scientific process as it is—with its limitations and potential pitfalls as well as its fun side, such as serendipitous discoveries and hilarious blunders,” Bosch writes.
Her article explains how they are trying to fill this gap with a new graduate science program, now in its second year. It’s called R3 because “our students learn to apply rigor to their design and conduct of experiments; view their work through the lens of social responsibility; and to think critically, communicate better, and thus improve reproducibility.”
“MOBILE CSR ACTIVITIES IN CRISES: AN EXAMINATION OF GRATIFICATIONS, CSR MOTIVES, SOCIAL MEDIA USE ON MOBILE DEVICES, AND RELATIONSHIP OUTCOMES”; Yang Cheng et al; Presented at 68th Annual Conference of the International Communication Association , Prague, Czech Republic, May 2018.
“Companies that engage in corporate social responsibility efforts during and after a disaster can build strong relationships with consumers,” says co-author Yang Cheng, an assistant professor of communication at North Carolina State University. “This is particularly true if companies are communicating their efforts through social media aimed at mobile device users—but only if their efforts appear altruistic.”
This conclusion comes from the investigators’ online, nationally representative survey asking 1,433 U.S. adults why people use social media during and after a natural disaster like hurricanes; how frequently they used social media to seek or share information during a crisis; the extent to which they shared information on crisis-related corporate social responsibility efforts; how they perceive the motives of relevant companies; and how they feel about the companies themselves.
The researchers found a strong link between how social media users viewed corporate social responsibility motives and how they viewed the companies engaged in those efforts
“What organizations can do,” advises Prof. Cheng, “is understand and value public perspectives; utilize the organization’s various social/mobile media platforms; show care and empathy; be honest; be open
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“Most PhD curricula are unlikely to nurture the big thinkers and creative problem-solvers that society needs.”
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and transparent in providing useful and timely information; and engage in actual dialogue with stakeholders both during and post crisis.”
BLOCKCHAIN: The future is here; MIT Technology Review special report, May/June 2018.
This first in Technology Review’s switch to single-topic bimonthly issues is devoted to the blockchain universe. Its three parts cover:
• “How We Got Here,” including blockchain after the bubble bursts, the case against crypto currencies, how a blockchain works, the top 12 digital “coins,” and a glossary of crypto jargon.
• “Where We Are Now,” including bitcoin mining in Quebec, blockchain security, restoring identity in a Jordan refugee camp, blockchain devotees, crypto crime, and why more women aren’t in blockchain tech.
• “What Comes Next,” including how Bitcoin could become irrelevant, one way initial coin offerings (ICOs) could contribute to the economy, and a science fiction vision of a blockchain-based future.
Digital Natives Lead 2018’s Most Innovative Companies
Once again Apple, Google and Microsoft top Boston Consulting Group’s list of 50 Most Innovative Companies. Among the other 2018 top 10, Alibaba Group and Uber are new. And seven of the top 10 are what BCG hails as “digital natives and thus digital innovators by definition.”
The BCG report, “The Most Innovative Companies 2018,” bcg.com, observes that shifting to digital innovation is difficult, requiring “big changes in strategy, operations, and organization.” The report discusses how digital strategy transforms innovation strategy, how it impacts operations, and how to organize for digital innovation. Auto Alliance To Invest $1B for Open Innovation
A Renault-Nissan-Mitsubishi auto alliance has launched a corporate venture capital fund planning to invest up to $1 billion to support openinnovation over the next five years.
In its first year, according to the announcement, Alliance Ventures (http://www.alliance-2022.com/ventures) expects to invest up to $200 million in start-ups and open innovation partnerships with technology entrepreneurs focused on new mobility, including vehicle electrification, autonomous systems, connectivity, and artificial intelligence.
In April it announced joining DiDi Auto Alliance, formed by the Chinese mobile transportation platform DiDi Chuxing. The DIDI alliance aims “to transform the business model of the automotive industry, and establish itself as the world’s largest full-capacity vehicle operator platform.”
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Researching Bias in Engineering Education
North Carolina State U researchers have begun a study of perceived bias in engineering education across the country. With funding from the National Science Foundation’s Directorate for Engineering, they will be interviewing and surveying engineering graduate students to understand and address how the students may feel stigmatized due to their race, gender, sexual orientation, or religion.
“One thing we want to capture here is how perceived bias affects the development of engineering identity in graduate students,” says Cheryl Cass, co-principal investigator of the project and director of undergraduate programs in NC State’s Department of Materials Science and Engineering. “Some previous studies suggest that self-identifying as an engineer can help engineering students persevere and succeed. We want to know if and how perceived bias influences this.”
The researchers intend to develop a suite of best practices that can be implemented by universities to reduce perceived bias in graduate engineering programs, and possibly other STEM graduate programs.
Call State of Cybersecurity Grim
Cybersecurity is only going to get worse, experts attending the annual RSA security conference in April told siliconAngle.com. According to Managing Editor Paul Gillin’s April 14 report, the tech news site asked a cross-section of attendees whether the battle against cyber criminals is being won and, if not, what can be done about it. “The glum consensus of the experts was nearly unanimous: Not only are we losing the war, but the scope and severity of successful attacks is accelerating.”
Said Gartner Inc. security analyst Lawrence Pingree: “There is no such thing as winning, only deflecting attackers and dealing with the ramifications of breaches.”
Still, siliconAngle found general agreement that greater attention to such security basics as strong passwords and avoiding clicking on unknown links “could probably choke off 90% of attacks.”
Foreign Student Visas Dropped in 2017
In the year ended Sept. 30, 2017, the State Department issued 393,573 student visas, down 17% from fiscal 2016 and nearly 40% below the 2015 peak, reported The Wall Street Journal on March 11.
While competition from schools in other countries and less support for foreign study by some governments contributed to the drop, “immigration attorneys and school officials say Trump administration policies are making the U.S. a tougher destination for foreigners and point to stricter scrutiny of those who do apply,” wrote Laura Meckler and Melissa Korn.
Entrepreneurs Remain Upbeat
Entrepreneurs are optimistic about their current and future performance according to a Kauffman Foundation national online survey of 2,165 business owners conducted early in 2018. For instance, 67% of the first-
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year entrepreneurs said their businesses performed well in 2017 while 88% predicted they would also do well in 2018. Ninety percent expect greater profits in 2018.
Nearly all respondents felt the government should spend more time supporting business owners but most would prefer it support a business-friendly environment rather than spending time on grants and funding.
Kauffman’s survey report, available at https://www.kauffman.org/what-we-do/entrepreneurship/state-of-entrepreneurship-2018, was released as part of the foundation’s national effort to make the voices of all entrepreneurs heard by policymakers around the country.
“Encouraging entrepreneurship begins with listening to entrepreneurs, helping to raise their voices and removing the barriers that block them from starting and growing their businesses,” said the foundation’s president and CEO Wendy Guillies. “The goal is to make entrepreneurship accessible to every interested American, to infuse it into the economy.”
NSF Budget Will Continue “Big Ideas” Funding
Besides continuing to support programs that help maintain U.S. preeminence in innovation, the National Science Foundation says its $7.47 billion FY 2019 budget request would advance its “10 Big Ideas for Future Investments” in that year.
NSF would commit $30 million to each of these six research-focused Big Ideas: Harnessing the Data Revolution; The Future of Work at the Human Technology Frontier; Windows on the Universe: The Era of Multi-messenger Astrophysics; The Quantum Leap: Leading the Next Quantum Revolution; Understanding the Rules of Life : Predicting Phenotype; and Navigating the New Arctic .
NSF says its annual budget would represent approximately 27% of the total federal budget for basic research conducted at U.S. colleges and universities —60% when medical research supported by the National Institutes of Health is excluded.
NC State Gains Quantum Computing Hub
In May, NC State became the first North American university to join IBM’s Q Network™, which provides early access to IBM Q commercial quantum computing systems. The NC State hub will collaborate with industry and affiliates to explore quantum computing and help grow its ecosystem, according to the IBM announcement.
“The hub will create a unique opportunity for NC State to address its strategic plan of supporting interdisciplinary scholarship and preparing students for the future,” said Alan Rebar, vice chancellor for research and innovation at NC State. “The hub will also drive new curriculum development at NC State, focused on quantum computing,” he said.
If Bill Gates Attended Harvard Today
The famous 1975 dropout would be studying artificial intelligence, Gates told students during an April tour of the Harvard Science Center. He also bemoaned “the anti-science problem,” adding, “We need to push back.”
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