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Building the necessary skills for digital transformation



Building the necessary skills for digital transformation

Daniela: Absolutely. It’s a total driver for innovation and it is also a driver to create something like a company memory of expertise and knowledge. Because you can bring together through one single point of entry, a universe of learning opportunities to the people.

You have so many great people and organizations that can contribute with latest insights, topics that they want to position and bring to the people. We haven’t had that in the past. Imagine a company like Siemens, a huge technology company active in so many industries. It means that we need to bring together learning opportunities from, let’s say, a functional perspective. So, if you are in finance or in supply chain, we need to then also complete it by, we call it cross-functional learning opportunities, which are topics that are relevant for everybody like languages or communication. We also have a whole learning landscape available on technology topics, on product-specific topics, on market-specific topics. It’s a huge landscape of learning opportunities, and everybody needs a subset, and everybody needs a very individual specialized subset. That is a huge benefit to be able to tailor it to that. And by having such an approach, I must also say it’s much more efficient and productive because it saves time and money. People can have access to a whole universe. They don’t have to travel, don’t have to then encounter programs where maybe only a certain percentage of it is relevant to them. It’s really helpful also to drive the overall business success.

Laurel: And part of that business success is digital transformation, right? Adopting and rolling out new technologies like automation and artificial intelligence. This will create a new division of labor between humans and machines, which will disrupt jobs globally. But as these jobs evolve, new roles will be created with people having specific advantages over machines and AI like managing and decision making and communicating and interacting — all of those things that humans are really good at. How can business people prepare and prepare their employees for this shift from automation?

Daniela: Yeah, I think it is something that accompanied us already since quite a few years. But there, again, the speed and also the level of skills needed has increased so significantly. I would say it’s almost like a bouquet of things that you can do and should do. You need to, as a company, create an identity and first of all, say that you really think learning and individual growth is super important. It is a priority for the company, and you need to give it a positive spin. It is there for you, it is there to support you, it starts with you. That is why we have initiated a company-wide campaign that we call MyGrowth.

It’s much more than a campaign, it’s an overall concept and approach. But it is really meant to inspire and engage people to try out the different experiences that we provide and help them to navigate and give orientation what they should and can use. Then we have also initiated a target on learning hours because we really wanted to nudge people and say, “Look, it’s important that you take the time and that you take it as a priority.”

With regard to the specific skills that you were mentioning around automation and digitalization, we then can include specific strategic topics that we push to our people. We drive awareness campaigns through learning opportunities. Those can be targeted for certain audiences because people also need different skill levels. Or we can push it at scale. This is a highly flexible system. If I may give you an example, we have one pocket in our businesses that is called Digital Industries Software. It fits very nicely to what you were mentioning. The CEO of that business last year said we are in a software business, so AI is a major driver for everything that we are doing. Therefore, my whole organization needs to understand what first of all, artificial intelligence is, let’s say on a very generic level. But also, people need to understand how we are using it as a technology internally, but also as a driver for our business and software solutions. And then we created different learning paths for different expertise layers, and could therefore, bring the whole topic in a very comprehensive manner to thousands of people of our Digital Industries business.

Laurel: So, you are doing two things. One, you’re pushing out what you think that everyone needs to know and learn, artificial intelligence being a big topic. But then how do you then also do assessments of people and their skills to identify skill gaps and then align learning programs with the business strategy to basically not just get a return on investment? Of course, everything does come back to profit, but also return on investment on the employee’s time and expertise. Because that is also something you’re growing.

Daniela: Yes. And the skills topic is a very hot one, I can tell you. It’s all over the place and coming from very different lenses and use cases. Technology plays a major role. A platform-based learning ecosystem with a learning experience platform at the core enables you to gain insights that we never had in the past. We can see what interests people. We can see why and for what are they engaging in learning, what are they then actually learning or what are they not learning, and then therefore, leaving. If you then multiply that and you see that over the overall workforce, you see also what are hot topics, what are skills that are coming on the horizon. You can see that in certain communities. We have certain communities that are, for instance, we call them digital talents, like tech talents. And there, you already see what the next topics are that will come on the horizon. And then we can match as a learning function, do we already have the right learning opportunities for the topics that are being searched for? That is one thing. But that is more the bottom-up part of it that is super important.


The Blue Technology Barometer 2022/23



The Blue Technology Barometer 2022/23

Overall ranking



The overall rankings tab shows the performance of the examined
economies relative to each other and aggregates scores generated
across the following four pillars: ocean environment, marine activity,
technology innovation, and policy and regulation.

This pillar ranks each country according to its levels of
marine water contamination, its plastic recycling efforts, the
CO2 emissions of its marine activities (relative to the size
of its economy), and the recent change of total emissions.

This pillar ranks each country on the sustainability of its
marine activities, including shipping, fishing, and protected

This pillar ranks each country on its contribution to ocean
sustainable technology research and development, including
expenditure, patents, and startups.

This pillar ranks each country on its stance on ocean
sustainability-related policy and regulation, including
national-level policies, taxes, fees, and subsidies, and the
implementation of international marine law.

Get access to technology journalism that matters.

MIT Technology Review offers in-depth reporting on today’s most MIT
Technology Review offers in-depth reporting on today’s most
important technologies to prepare you for what’s coming next.




MIT Technology Review Insights would like to thank the following
individuals for their time, perspective, and insights:

  • Valérie Amant, Director of Communications, The SeaCleaners
  • Charlotte de Fontaubert, Global Lead for the Blue Economy, World Bank Group
  • Ian Falconer, Founder, Fishy Filaments
  • Ben Fitzgerald, Managing Director, CoreMarine
  • Melissa Garvey, Global Director of Ocean Protection, The Nature Conservancy
  • Michael Hadfield, Emeritus Professor, Principal Investigator, Kewalo Marine Laboratory, University of Hawaii
    at Mānoa
  • Takeshi Kawano, Executive Director, Japan Agency for Marine-Earth Science and Technology
  • Kathryn Matthews, Chief Scientist, Oceana
  • Alex Rogers, Science Director, REV Ocean
  • Ovais Sarmad, Deputy Executive Secretary, United Nations Framework Convention on Climate Change
  • Thierry Senechal, Managing Director, Finance for Impact
  • Jyotika Virmani, Executive Director, Schmidt Ocean Institute
  • Lucy Woodall, Associate Professor of Marine Biology, University of Oxford, and Principal Scientist at Nekton


Methodology: The Blue Technology Barometer 2022/23

Now in its second year, the Blue Technology Barometer assesses and ranks how each of the world’s largest
maritime economies promotes and develops blue (marine-centered) technologies that help reverse the impact of
climate change on ocean ecosystems, and how they leverage ocean-based resources to reduce greenhouse gases and
other effects of climate change.

To build the index, MIT Technology Review Insights compiled 20 quantitative and qualitative data indicators
for 66 countries and territories with coastlines and maritime economies. This included analysis of select
datasets and primary research interviews with global blue technology innovators, policymakers, and
international ocean sustainability organizations. Through trend analysis, research, and a consultative
peer-review process with several subject matter experts, weighting assumptions were assigned to determine the
relative importance of each indicator’s influence on a country’s blue technology leadership.

These indicators measure how each country or territory’s economic and maritime industries have affected its
marine environment and how quickly they have developed and deployed technologies that help improve ocean
health outcomes. Policy and regulatory adherence factors were considered, particularly the observance of
international treaties on fishing and marine protection laws.

The indicators are organized into four pillars, which evaluate metrics around a sustainability theme. Each
indicator is scored from 1 to 10 (10 being the best performance) and is weighted for its contribution to its
respective pillar. Each pillar is weighted to determine its importance in the overall score. As these research
efforts center on countries developing blue technology to promote ocean health, the technology pillar is
ranked highest, at 50% of the overall score.

The four pillars of the Blue Technology Barometer are:

Carbon emissions resulting from maritime activities and their relative growth. Metrics in this pillar also
assess each country’s efforts to mitigate ocean pollution and enhance ocean ecosystem health.

Efforts to promote sustainable fishing activities and increase and maintain marine protected areas.

Progress in fostering the development of sustainable ocean technologies across several relevant fields:

  • Clean innovation scores from MIT Technology Review Insights’ Green Future Index 2022.
  • A tally of maritime-relevant patents and technology startups.
  • An assessment of each economy’s use of technologies and tech-enabled processes that facilitate ocean

Commitment to signing and enforcing international treaties to promote ocean sustainability and enforce
sustainable fishing.

About Us

MIT Technology Review was founded at the Massachusetts Institute of Technology in 1899. MIT Technology Review
Insights is the custom publishing division of MIT Technology Review. We conduct qualitative and quantitative
research and analysis worldwide and publish a wide variety of content, including articles, reports,
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What Shanghai protesters want and fear



What Shanghai protesters want and fear

You may have seen that nearly three years after the pandemic started, protests have erupted across the country. In Beijing, Shanghai, Urumqi, Guangzhou, Wuhan, Chengdu, and more cities and towns, hundreds of people have taken to the streets to mourn the lives lost in an apartment fire in Urumqi and to demand that the government roll back its strict pandemic policies, which many blame for trapping those who died. 

It’s remarkable. It’s likely the largest grassroots protest in China in decades, and it’s happening at a time when the Chinese government is better than ever at monitoring and suppressing dissent.

Videos of these protests have been shared in real time on social media—on both Chinese and American platforms, even though the latter are technically blocked in the country—and they have quickly become international front-page news. However, discussions among foreigners have too often reduced the protests to the most sensational clips, particularly ones in which protesters directly criticize President Xi Jinping or the ruling party.

The reality is more complicated. As in any spontaneous protest, different people want different things. Some only want to abolish the zero-covid policies, while others have made direct calls for freedom of speech or a change of leadership. 

I talked to two Shanghai residents who attended the protests to understand what they experienced firsthand, why they went, and what’s making them anxious about the thought of going again. Both have requested we use only their surnames, to avoid political retribution.

Zhang, who went to the first protest in Shanghai after midnight on Saturday, told me he was motivated by a desire to let people know his discontent. “Not everyone can silently suffer from your actions,” he told me, referring to government officials. “No. People’s lives have been really rough, and you should reflect on yourself.”

In the hour that he was there, Zhang said, protesters were mostly chanting slogans that stayed close to opposing zero-covid policies—like the now-famous line “Say no to covid tests, yes to food. No to lockdowns, yes to freedom,” which came from a protest by one Chinese citizen, Peng Lifa, right before China’s heavily guarded party congress meeting last month. 

While Peng hasn’t been seen in public since, his slogans have been heard and seen everywhere in China over the past week. Relaxing China’s strict pandemic control measures, which often don’t reflect a scientific understanding of the virus, is the most essential—and most agreed-upon—demand. 

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Biotech labs are using AI inspired by DALL-E to invent new drugs



Biotech labs are using AI inspired by DALL-E to invent new drugs

Today, two labs separately announced programs that use diffusion models to generate designs for novel proteins with more precision than ever before. Generate Biomedicines, a Boston-based startup, revealed a program called Chroma, which the company describes as the “DALL-E 2 of biology.”

At the same time, a team at the University of Washington led by biologist David Baker has built a similar program called RoseTTAFold Diffusion. In a preprint paper posted online today, Baker and his colleagues show that their model can generate precise designs for novel proteins that can then be brought to life in the lab. “We’re generating proteins with really no similarity to existing ones,” says Brian Trippe, one of the co-developers of RoseTTAFold.

These protein generators can be directed to produce designs for proteins with specific properties, such as shape or size or function. In effect, this makes it possible to come up with new proteins to do particular jobs on demand. Researchers hope that this will eventually lead to the development of new and more effective drugs. “We can discover in minutes what took evolution millions of years,” says Gevorg Grigoryan, CEO of Generate Biomedicines.

“What is notable about this work is the generation of proteins according to desired constraints,” says Ava Amini, a biophysicist at Microsoft Research in Cambridge, Massachusetts. 

Symmetrical protein structures generated by Chroma


Proteins are the fundamental building blocks of living systems. In animals, they digest food, contract muscles, detect light, drive the immune system, and so much more. When people get sick, proteins play a part. 

Proteins are thus prime targets for drugs. And many of today’s newest drugs are protein based themselves. “Nature uses proteins for essentially everything,” says Grigoryan. “The promise that offers for therapeutic interventions is really immense.”

But drug designers currently have to draw on an ingredient list made up of natural proteins. The goal of protein generation is to extend that list with a nearly infinite pool of computer-designed ones.

Computational techniques for designing proteins are not new. But previous approaches have been slow and not great at designing large proteins or protein complexes—molecular machines made up of multiple proteins coupled together. And such proteins are often crucial for treating diseases.  

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