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An inside look at how trust accelerates transformation

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With thousands of developers, publishers, authors, designers, production houses and distributors, Microsoft’s Xbox gaming platform is a complex ecosystem of relationships. Collaboration across this ecosystem is key to producing a high-quality product that attracts the best talent and satisfies consumers—but Microsoft recognized points of friction that needed to be addressed. 

A multitude of manual processes and siloed systems meant that developers and publishers couldn’t link complex calculations for royalties to the underlying data. As a result, they had to spend time and resources reconciling, validating and recalculating royalties to verify accuracy. 

To cut through complexity and increase trust in the data, Microsoft and EY partnered to co-develop the first blockchain-based financial system of records for processing end-to-end royalty transactions, from contract creation through to integration with SAP for payments. The blockchain solution provides near real-time access to trusted transaction data from source systems to game publishers.

The upshot? Publishers can access information on royalties earned in just four minutes instead of 45 days after month end. Royalties administration costs have been slashed. There’s greater visibility of the underlying data. Microsoft benefits from faster, more efficient processes and lower operational costs. 

With trust, everything moves more smoothly. Collaboration is easier. Innovation drives value. Technology can be deployed at speed. But getting to this is far from easy.

We are living in a time of increasingly intelligent technologies, when an organization’s ability to be trusted really matters. But the way data and intelligent technologies such as AI are being used is creating significant trust gaps. For example, the public feels that intelligent technology is moving too fast and that regulators can’t keep up, as documented in the 2020 Edelman Trust Barometer

There are plenty of high-profile examples of data misuse and unintended outcomes from AI usage that have contributed to these gaps. One example was this June when an AI tool to reconstruct pixelated photos turned a photo of Barack Obama into a white man. It became a matter of hot debate in the AI community: was the bias towards creating more photos of white people than people of color the result of incomplete data or indicative of the racial bias baked into AI from non-diverse datasets and development teams?

Trust gaps have reframed the question of “Can tech do this?” into “Should tech do this?” It’s no longer about capabilities. It’s about trust in the intelligence that a business uses, and that customers, markets, regulators and ecosystems rely on. Can companies and government organizations ensure the outcomes of their technologies? Without trust, the ability of an organization to operate and innovate is diminished.

Trust in data and technologies results from action. There are methods and techniques that embed trust into data, systems and business models to create sustained value. At EY, we call this Trusted Intelligence.

Trust has to be designed in from the outset. Trusted Intelligence embeds trust in a tangible way that embraces behaviors, processes, business models and outcomes as data moves through the organization — accelerating transformation and lasting value.

Going back to the Xbox story, we can see how trust was embedded into the intelligence of the business: 

  • Data from a multitude of manual workflows and unintegrated systems has been replaced with trusted data 
  • Trusted data is also created by automating complex royalty calculations, product tokenization and onboarding smart contracts using AI based on secure cloud technologies
  • Trust is maintained through the blockchain-based system of record that generates invoices and statements with integration to SAP for settlement and processing of payments, as well as post-accounting journals
  • And finally, trust is embedded into how people work by applying clear rules and transparent processes

As businesses seek competitive advantage, applying Trusted Intelligence offers a new frontier of opportunities to accelerate digital transformation.  

Accelerated transformation

While digital transformation was well underway prior to the pandemic, Covid-19 stepped up the pace. In a recent EY webcast on the impact of Covid-19 with nearly 2000 participants, 82% said they were accelerating digital transformation.

This confirms what we’re experiencing with our clients in the market. We know those achieving radical and exponential value creation are responding to three key drivers: 

  • The ability to put humans at the center of what they do: when it comes to customers, it’s not “How do we get more customers to buy what we make or do?” but “How do we give customers more of what they want?” This new mindset is backed by engaged, motivated employees.   
  • Deploying technology at speed: today’s customers and employees demand speed. This means automation through AI and other intelligent technologies, as well as cloud-based services. It means using agile methodologies and technology that helps you respond to dynamic conditions. 
  • Innovating at scale: organizations need to innovate on two levels – survival today and success tomorrow. Collaboration is the name of the game, for example through ecosystems and alliances. Innovative ideas must be built using large volumes of data, intelligent technologies and cloud infrastructure that are trusted. 

Each of these drivers is amplified by Trusted Intelligence. Embedding trust is how organizations can reduce trust gaps and accelerate their digital transformation. 

Putting Trusted Intelligence onto your agenda

Trusted Intelligence and value are inextricably linked, and more value builds more trust. There are some fundamental questions that organizations and governments need to address to close trust gaps, take advantage of transformation and earn competitive advantage: 

  • Do I trust my data, technologies and automated processes? 
  • Do I trust my ecosystems’ data, technologies and automated processes? 
  • Does my ecosystem trust my data, technologies and automated processes?  

These questions define the strategies, investments and actions of organizations as they reshape their operating models.  

Conclusion 

As businesses and governments transform to meet new challenges, it’s essential to embed Trusted Intelligence into the core of operations. As the Xbox example shows, intelligent technologies such as blockchain can build trust into the data and the platform, increasing transparency. With trusted data and technologies, a business can move forward with confidence and at speed. 

Enterprises powered by trust will be able to deliver on all three transformation drivers: people, technology and innovation. They’ll be able to leapfrog their competitors. To shape new markets. To lead into better futures.

This content was produced by EY. It was not written by MIT Technology Review’s editorial staff.

Lyron Foster is a Hawaii based African American Musician, Author, Actor, Blogger, Filmmaker, Philanthropist and Multinational Serial Tech Entrepreneur.

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Elon Musk says Tesla Semi is ready for production, but limited by battery cell output

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Tesla CEO Elon Musk said on the company’s 2020 Q4 earnings call that all engineering work is now complete on the Tesla Semi, the freight-hauling semi truck that the company is building with an all-electric powertrain. The company expects to begin deliveries of Tesla Semi this year, the company said in its Q4 earnings release, and Musk said the only thing limiting their ability to produce them now is the availability of battery cells.

“The main reason we have not accelerated new products – like for example Tesla Semi – is that we simply don’t have enough cells for it,” Musk said. “If we were to make the Semi right now, and we could easily go into production with the Semi right now, but we would not have enough cells for it.”

Musk added that the company does expect to have sufficient cell volume to meet its needs once it goes into production on its 4680 battery pack, which is a new custom cell design it created with a so-called ‘tables’ design that allows for greater energy density and therefore range.

“A Semi would use typically five times the number of cells that a car would use, but it would not sell for five times what a car would sell for, so it kind of would not make sense for us to do the Semi right now,” Musk said. “But it will absolutely make sense for us to do it as soon as we can address the cell production constraint.”

That constraint points to the same conclusion for the possibility of Tesla developing a van, Musk added, and the lifting of the constraint will likewise make it possible for Tesla to pursue the development of that category of vehicle, he said.

Tesla has big plans for “exponentially” ramping cell production, with a goal of having production capacity infrastructure in place for a Toal of 200 gigawatt hours per year by 2022, and a target of being able to actually produce around 40% of that by that year (with future process improvements generating additional gigawatt hours of cell capacity  in gradual improvements thereafter).

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Pro-Trump Twitter figure arrested for spreading vote-by-text disinformation in 2016

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The man behind a once-influential pro-Trump account is facing charges of election interference for allegedly disseminating voting disinformation on Twitter in 2016.

Federal prosecutors allege that Douglass Mackey, who used the name “Ricky Vaughn” on Twitter, encouraged people to cast their ballot via text or on social media, effectively tricking others into throwing away those votes.

According to the Justice Department, 4,900 unique phone numbers texted a phone number Mackey promoted in order to “vote by text.” BuzzFeed reported the vote-by-text scam at the time, noting that many of the images were photoshopped to look like official graphics from Hillary Clinton’s presidential campaign.

Some of those images appeared to specifically target Black and Spanish-speaking Clinton supporters, a motive that tracks with the account’s track record of white supremacist and anti-Semitic content. The account was suspended in November 2016.

At the time, the mysterious account quickly gained traction in the political disinformation ecosystem. HuffPost revealed that the account was run by Mackey, the son of a lobbyist, two years later.

“… His talent for blending far-right propaganda with conservative messages on Twitter made him a key disseminator of extremist views to Republican voters and a central figure in the alt-right’ white supremacist movement that attached itself to Trump’s coattails,” HuffPost’s Luke O’Brien reported.

Mackey, a West Palm Beach resident, was taken into custody Wednesday in Florida.

“There is no place in public discourse for lies and misinformation to defraud citizens of their right to vote,” Acting U.S. Attorney for the Eastern District of New York Seth D. DuCharme said.

“With Mackey’s arrest, we serve notice that those who would subvert the democratic process in this manner cannot rely on the cloak of Internet anonymity to evade responsibility for their crimes.”

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Tesla is willing to license Autopilot and has already had “preliminary discussions” about it with other automakers

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Tesla is open to licensing its software, including its Autopilot highly-automated driving technology, and the neural network training it has built to improve its autonomous driving technology. Tesla CEO Elon Musk revealed those considerations on the company’s Q4 earnings call on Wednesday, adding that the company has in fact already “had some preliminary discussions about licensing Autopilot to other OEMs.”

The company began rolling out its beta version of the so-called ‘full self-driving’ or FSD version of Autopilot late last year. The standard Autopilot features available in general release provide advanced driver assistance (ADAS) which provide essentially advanced cruise control capabilities designed primarily for use in highway commutes. Musk said on the call that he expects the company will seek to prove out its FSD capabilities before entering into any licensing agreements, if it does end up pursuing that path.

Musk noted that Tesla’s “philosophy is definitely not to create walled gardens” overall, and pointed out that the company is planning to allow other automakers to use its Supercharger networks, as well as its autonomy software. He characterized Tesla as “more than happy to license” those autonomous technologies to “other car companies,” in fact.

One key technical hurdle required to get to a point where Tesla’s technology is able to demonstrate true reliability far surpassing that of a standard human driver is transition the neural networks operating in the cars and providing them with the analysis that powers their perception engines is to transition those to video. That’s a full-stack transition across the system away from basing it around neural nets trained on single cameras and single frames.

To this end, the company has developed video labelling software that has had “a huge effect on the efficiency of labeling,” with the ultimate aim being enabling automatic labeling. Musk (who isn’t known for modesty around his company’s achievements, it should be said) noted that Tesla believes “it may be the best neural net training computer in the world by possibly an order of magnitude,” adding that it’s also “something we can offer potentially as a service.”

Training huge quantities of video data will help Tesla push the reliability of its software from 100% that of a human driver, to 200% and eventually to “2,000% better than the average human,” Musk said, while again suggesting that it won’t be a technological achievement the company is interested into keeping to themselves.

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