Daily Tech Digest - May 16, 2023

Law enforcement crackdowns and new techniques are forcing cybercriminals to pivot

Because of stepped-up law enforcement efforts, cybercriminals are also facing a crisis in cashing out their cryptocurrencies, with only a handful of laundering vehicles in place due to actions against crypto-mixers who help obfuscate the money trail. "Eventually, they'll have to cash out to pay for their office space in St. Petersburg to pay for their Lambos. So, they're going to need to find an exchange," Burns Coven said. Cybercriminals are just sitting on their money, like stuffing money under the mattress. "It's been a tumultuous two years for the threat actors," she said. "A lot of law enforcement takedowns, challenging operational environments, and harder to get funds. And we're seeing this sophisticated laundering technique called absolutely nothing doing, just sitting on it." Despite the rising number of challenges, "I don't think there's a mass exodus of threat actors from ransomware," Burns Coven tells CSO, saying they are shifting tactics rather than exiting the business altogether. 

5 IT management practices certain to kill IT productivity

Holding people accountable is root cause analysis predicated on the assumption that if something goes wrong it must be someone’s fault. It’s a flawed assumption because most often, when something goes wrong, it’s the result of bad systems and processes, not someone screwing up. When a manager holds someone accountable they’re really just blame-shifting. Managers are, after all, accountable for their organization’s systems and processes, aren’t they? Second problem: If you hold people accountable when something goes wrong, they’ll do their best to conceal the problem from you. And the longer nobody deals with a problem, the worse it gets. One more: If you hold people accountable whenever something doesn’t work, they’re unlikely to take any risks, because why would they? Why it’s a temptation: Finding someone to blame is, compared to serious root cause analysis, easy, and fixing the “problem” is, compared to improving systems and practices, child’s play. As someone once said, hard work pays off sometime in the indefinite future, but laziness pays off right now.

How AI ethics is coming to the fore with generative AI

The discussion of AI ethics often starts with a set of principles guiding the moral use of AI, which is then applied in responsible AI practices. The most common ethical principles include being human-centric and socially beneficial, being fair, offering explainability and transparency, being secure and safe, and showing accountability. ... “But it’s still about saving lives and while the model may not detect everything, especially the early stages of breast cancer, it’s a very important question,” Sicular says. “And because of its predictive nature, you will not have everyone answering the question in the same fashion. That makes it challenging because there’s no right or wrong answer.” ... “With generative AI, you will never be able to explain 10 trillion parameters, even if you have a perfectly transparent model,” Sicular says. “It’s a matter of AI governance and policy to decide what should be explainable or interpretable in critical paths. It’s not about generative AI per se; it's always been a question for the AI world and a long-standing problem.”

Design Patterns Are A Better Way To Collaborate On Your Design System

You probably don’t think of your own design activities as a “pattern-making” practice, but the idea has a lot of very useful overlap with the practice of making a design system. The trick is to collaborate with your team to find the design patterns in your own product design, the parts that repeat in different variations that you can reuse. Once you find them, they are a powerful tool for making design systems work with a team. ... All designers and developers can make their design system better and more effective by focusing on patterns first (instead of the elements), making sure that each is completely reusable and polished for any context in their product. “Pattern work can be a fully integrated part of both getting some immediate work done and maintaining a design system. ... This kind of design pattern activity can be a direct path for designers and developers to collaborate, to align the way things are designed with the way they are built, and vice-versa. For that purpose, a pattern does not have to be a polished design. It can be a rough outline or wireframe that designers and developers make together. It needs no special skills and can be started and iterated on by all. 

Digital Twin Technology: Revolutionizing Product Development

Digital twin technology accelerates product development while reducing time to market and improving product performance, Norton says. The ability to design and develop products using computer-aided design and advanced simulation techniques can also facilitate collaboration, enable data driven decision making, engineer a market advantage, and reduce design churn. “Furthermore, developing an integrated digital thread can enable digital twins across the product lifecycle, further improving product design and performance by utilizing feedback from manufacturing and the field.” Using digital twins and generative design upfront allows better informed product design, enabling teams to generate a variety of possible designs based on ranked requirements and then run simulations on their proposed design, Marshall says. “Leveraging digital twins during the product use-cycle allows them to get data from users in the field in order to get feedback for better development,” she adds. Digital twin investments should always be aimed at driving business value. 

DevEx, a New Metrics Framework From the Authors of SPACE

Organizations can improve developer experience by identifying the top points of friction that developers encounter, and then investing in improving areas that will increase the capacity or satisfaction of developers. For example, an organization can focus on reducing friction in development tools in order to allow developers to complete tasks more seamlessly. Even a small reduction in wasted time, when multiplied across an engineering organization, can have a greater impact on productivity than hiring additional engineers. ... The first task for organizations looking to improve their developer experience is to measure where friction exists across the three previously described dimensions. The authors recommend selecting topics within each dimension to measure, capturing both perceptual and workflow metrics for each topic, and also capturing KPIs to stay aligned with the intended higher-level outcomes. ... The DevEx framework provides a practical framework for understanding developer experience, while the accompanying measurement approaches systematically help guide improvement.
While there are many companies with altruistic intentions, the reality is that most organizations are beholden to stakeholders whose chief interests are profit and growth. If AI tools help achieve those objectives, some companies will undoubtedly be indifferent to their downstream consequences, negative or otherwise. Therefore, addressing corporate accountability around AI will likely start outside the industry in the form of regulation. Currently, corporate regulation is pretty straightforward. Discrimination, for instance, is unlawful and definable. We can make clean judgments about matters of discrimination because we understand the difference between male and female, or a person’s origin or disability. But AI presents a new wrinkle. How do you define these things in a world of virtual knowledge? How can you control it? Additionally, a serious evaluation of what a company is deploying is necessary. What kind of technology is being used? Is it critical to the public? How might it affect others? Consider airport security. 

Prepare for generative AI with experimentation and clear guidelines

Your first step should be deciding where to put generative AI to work in your company, both short-term and into the future. Boston Consulting Group (BCG) calls these your “golden” use cases — “things that bring true competitive advantage and create the largest impact” compared to using today’s tools — in a recent report. Gather your corporate brain trust to start exploring these scenarios. Look to your strategic vendor partners to see what they’re doing; many are planning to incorporate generative AI into software ranging from customer service to freight management. Some of these tools already exist, at least in beta form. Offer to help test these apps; it will help teach your teams about generative AI technology in a context they’re already familiar with. ... To help discern the applications that will benefit the most from generative AI in the next year or so, get the technology into the hands of key user departments, whether it’s marketing, customer support, sales, or engineering, and crowdsource some ideas. Give people time and the tools to start trying it out, to learn what it can do and what its limitations are. 

Cyberdefense will need AI capabilities to safeguard digital borders

Speaking at CSIT's twentieth anniversary celebrations, where he announced the launch of the training scheme, Teo said: "Malign actors are exploiting technology for their nefarious goals. The security picture has, therefore, evolved. Malicious actors are using very sophisticated technologies and tactics, whether to steal sensitive information or to take down critical infrastructure for political reasons or for profit. "Ransomware attacks globally are bringing down digital government services for extended periods of time. Corporations are not spared. Hackers continue to breach sophisticated systems and put up stolen personal data for sale, and classified information." Teo also said that deepfakes and bot farms are generating fake news to manipulate public opinion, with increasingly sophisticated content that blur the line between fact and fiction likely to emerge as generative AI tools, such as ChatGPT, mature and become widely available. "Threats like these reinforce our need to develop strong capabilities that will support our security agencies and keep Singapore safe," the minister said. 

Five key signs of a bad MSP relationship – and what to do about them

Red flags to look out for here include overly long and unnecessarily complicated contracts. These are often signs of MSPs making lofty promises, trying to tie you into a longer project, and pre-emptively trying to raise bureaucratic walls to make accessing the services you are entitled to more complex. The advice here is simple – don’t rush the contract signing. Instead, ensure that the draft contract is passed through the necessary channels, so that all stakeholders have complete oversight. Also, do not be tempted by outlandish promises; think pragmatically about what you want to achieve with your MSP relationship, and make sure the contract reflects your goals. If you’re already locked into a contract, consider renegotiating specific terms. ... If projects are moving behind schedule and issues are coming up regularly, this is a sign that your project lacks true project management leadership. Of course, both parties will need some time when the project starts to get processes running smoothly, but if you’re deep into a contract and still experiencing delays and setbacks, this is a sign that all is not well at your MSP. 

Quote for the day:

"The greatest thing is, at any moment, to be willing to give up who we are in order to become all that we can be." -- Max de Pree

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