Daily Tech Digest - January 18, 2024

A tougher balancing act in 2024, the year of the CISO

What’s making things more difficult for CISOs? The ESG/ISSA data indicates that business aspects of running a cybersecurity program like working with the board, overseeing regulatory compliance, and managing a budget are primary contributing factors. This makes sense as the CISO role has evolved from technical overseer to business executive over the past few years. At the same time, organizations have increased their dependence on IT for automation, optimization, customer service, and digital transformation. ... Like their non-CISOs colleagues, CISOs are particularly stressed by things like an overwhelming workload, working with disinterested business managers, and keeping up with the security requirements of new business initiatives. It’s worth noting that 26% of CISOs are also stressed about monitoring the security status of third parties their organization does business with as compared with 12% of non-CISOs. Third-party relationships are often associated with business processes and therefore tied closely with business units. Unfortunately, security teams probably don’t have deep visibility into the day-to-day security performance at these firms. 

How do agile and DevOps interrelate?

Agile and DevOps have much in common. In fact, DevOps grew as an offshoot (or improvement) of agile, as many industry leaders found dysfunction in IT and software development. While incremental improvements support quality products, the competing objectives of individual IT workers lowered overall performance. To remedy the problem, developers proposed the more integrated approach of DevOps. Of course, the new philosophy offered different core values, which caused a split between two opposing communities. Developers grappled with what looked like conflicting philosophies, leading to the most common misconception about agile and DevOps: that they don’t interrelate. On the surface, the pundits have much to draw on. DevOps engineers focus on software scalability, speed, and team integration. Agile focuses on the slower, iterative process of software development, with more emphasis on continuous testing. More importantly, Agile silos individuals while DevOps integrates. Without the operability of DevOps, infrastructure responsibility falls to the wayside. But without the basic building blocks of the incremental, customer-focused method of agile, DevOps has no fundamental processes on which to stand.

AI Fraud Act Could Outlaw Parodies, Political Cartoons, and More

So just how broad is this bill? For starters, it applies to the voices and depictions of all human beings "living or dead." And it defines digital depiction as any "replica, imitation, or approximation of the likeness of an individual that is created or altered in whole or part using digital technology." Likeness means any "actual or simulated image… regardless of the means of creation, that is readily identifiable as the individual." Digital voice replica is defined as any "audio rendering that is created or altered in whole or part using digital technology and is fixed in a sound recording or audiovisual work which includes replications, imitations, or approximations of an individual that the individual did not actually perform." This includes "the actual voice or a simulation of the voice of an individual, whether recorded or generated by computer, artificial intelligence, algorithm, or other digital means, technology, service, or device." These definitions go way beyond using AI to create a fraudulent ad endorsement or musical recording. They're broad enough to include reenactments in a true-crime show, a parody TikTok account, or depictions of a historical figure in a movie.

Navigating digital transformation in insurance sector: Challenges, opportunities and innovations

Notable developments are the changes that regulators have come up with in cybersecurity, the Information Security Management, the connectivity management with the website, with the vendors and employees, and the digital transformation that they have pushed us to. Because today, everything is digitally handled, an employee actually meets a customer, and the customer fills the form digitally; there is no mechanical filling of forms, although that practice is still there in many parts of the country and in many companies also. Having said that the digital absorption has become higher in percentage. So, when we handle things digitally, you will have to think through, and therefore today, employees are forced to think through what are the controls they could have. Like we have introduced OTP, so each state’s customer is forced to think and answer questions on OTP. You have to give OTP for that, like a policy that I bought about last week, so I had to do six OTPs in that company. I was wondering why so many OTPs are required, but when I look at the way the processes were handled by the salesperson, it was quite effective and efficient, and at the same time, it’s all for the safety of the customer, that thought process is given to the customer.

Productivity Paradox: Productivity in the Age of Knowledge Work

We sometimes forget that every employee within an enterprise is, at their core, also a consumer. Their personal preferences, shaped by daily interactions with personal technology, inevitably spill over into their professional lives. Consequently, the ubiquity of Macs, iPhones and iPads in the consumer market has sparked a growing demand for these devices in the workplace. This shift has only been hastened by the “Bring Your Own Device” (BYOD) movement, wherein employees sought to use their trusted personal devices for professional tasks, yearning for the familiarity and ease of use they’ve grown accustomed to. Instead of resisting this tide, more and more forward-thinking enterprises are instead leaning in. For one, IT leaders have recognized that specific hardware platforms matter less these days as they shift more of their applications to the public cloud. Reliability is another major factor, especially for remote employees who don’t have an IT helpdesk at their disposal. And when our survey respondents were asked if they agreed or disagreed with the statement “Apple takes enterprise security, compliance, and privacy concerns more seriously than other vendors,” three-quarters of them concurred.

6 hot networking and data center skills for 2024

“The current rage in AI technology is more than just a fad,” Leary says. “It is delivering real measurable benefits to IT organizations and the businesses they serve. And there is no sign of slowdown on the horizon. Driven by pressing capacities and costs, physical data center designs are changing significantly” with generative AI. Organizations need IT staffers who can help assure that generative AI is provided the data, data processing, and data exchanges needed to deliver on its promise, Leary says. ... Knowledge about cyber security products and services—as well as the threats they guard against—never go out of fashion. Organizations are facing a barrage of threats against their networks and data centers, so finding people with related skills remains a high priority. “Companies are constantly having to pay attention to their security as more and more cyber attacks happen,” Vick says. “That is something that is not slowing down, so they are having to update their firewalls and other security features.” Enterprises are building out their security teams, in some cases looking for people to update their security posture with a variety of technologies.

Navigating data management modernisation to deliver the AI-ready tech stack of the future

Forward-thinking IT leaders already see a direct correlation between modernising the data management journey across the entire tech stack and facilitating the extraction of value from data at the speed and scale needed for real-time intelligence. The same Alteryx research suggests that digital transformation relating to AI and machine learning will be the number one characteristic of the future enterprise, and tech stack priorities are already shifting to reflect this. Generative AI, quantum computing and machine learning operations (MLOps) are cited as the technologies most likely to see the largest shift in accelerated adoption in the future. While it only seems a short time since the pandemic forced many organisations to accelerate transformation at breakneck speeds, the rise of AI-related technologies will reinfuse these transformations. Why? Because AI has lowered the barrier to delivering productivity gains by delivering data-driven insights with just a sentence or a prompt. With countless data-oriented AI technologies and intelligent systems already available, the ultimate goal of this transformation is to modernise the data management journey across the entire stack.

Continuous Quality Assurance: Strategizing Automated Regression Testing for Codebase Resilience

In times of QA software testing, automation regression processes can be enabled to autonomously identify any unexpected behaviors or regressions in the software. ... End-users anticipate a consistent and dependable performance from software, recognizing that any disruptions or failures can profoundly affect their productivity and overall user experience. The implementation of regression testing proves invaluable in identifying unintended consequences, validating bug fixes, upholding consistency across versions, and securing the success of continuous deployment. Through early identification and resolution of regressions, development teams can proactively safeguard against issues reaching end-users, thereby preserving the quality and reliability of their software. ... Automated regression testing can be strategized based on the complexity of the codebase for approaches like retesting everything, selective re-testing, and prioritized re-testing. Tools such as Functionize, Selenium, Watir, Sahi Pro, and IBM Rational Functional Tester can be used to automate regression testing and improve efficiency.

Sustainable Partnerships Pay Dividends

The first step in establishing highly effective partnerships, von Koeller says, is to identify what an organization hopes to achieve and establish a roadmap for meeting specific goals and metrics. This requires a focus on shared values and coordination across departments and groups. “You have to understand your footprint, understand what environmental impact an action has, and how to engage suppliers to achieve alignment around your targets,” she explains. Open and honest communication among partners is vital. Too often, larger companies fail to understand what suppliers can do and what they can’t do, particularly when they’re located in faraway countries, or a supply chain has numerous layers. Partners downstream and upstream face their own set of challenges -- environmental, political, and practical -- that can make it difficult to conform to strict standards. A particularly daunting aspect -- especially for smaller firms supplying raw materials or specialized components -- is onerous data collection and reporting requirements, Linich notes. As a result, smaller companies may require funding and technical assistance from larger partners, including aid in setting up software and IT systems that support sustainability.

Get started with Anaconda Python

The Anaconda distribution is a repackaging of Python aimed at developers who use Python for data science. It provides a management GUI, a slew of scientifically oriented work environments, and tools to simplify the process of using Python for data crunching. It can also be used as a general replacement for the standard Python distribution, but only if you’re conscious of how and why it differs from the stock version of Python. ... The most noticeable thing Anaconda adds to the experience of working with Python is a GUI, the Anaconda Navigator. It is not an IDE, and it doesn’t try to be one, because most Python-aware IDEs can register and use the Anaconda Python runtime themselves. Instead, the Navigator is an organizational system for the larger pieces in Anaconda. With the Navigator, you can add and launch high-level applications like RStudio or Jupyterlab; manage virtual environments and packages; set up “projects” as a way to manage work in Anaconda; and perform various administrative functions. Although the Navigator provides the convenience of a GUI, it doesn’t replace any command-line functionality in Anaconda, or in Python generally. 

Quote for the day:

"Leaders are more powerful role models when they learn than when they teach." -- Rosabeth Moss Kantor

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