Daily Tech Digest - July 09, 2023

Data should be a first-class citizen in the cloud

A close cousin of the interoperability problem, data access and control are limited in many cloud environments if not designed properly and can prevent organizations from truly harnessing their business data. There doesn’t seem to be a middle ground here; either data is entirely accessible or not at all. Mostly, the controller is turned off and valuable data goes unleveraged and systems are underoptimized. You only need to look at the rise of generative AI systems to understand how this limitation affects the value of these systems. If the data is not accessible, then the knowledge engines can’t be appropriately trained. You’ll have dumb AI. This lack of control is due to opaque data ownership models and limited data processing and storage control. The solution is for organizations to create greater transparency and control over their data. This includes defining access privileges, managing encryption, and deciding how and where data is stored. This would ensure that data owners retain sovereignty and information is still available.

Where Data Governance Must Focus in AI Era

In recent years, the ethical implications of AI have come to the forefront of public discussion. Data governance reinforces the importance of adhering to ethical practices in the development and deployment of AI systems. Transparency and accountability should be the pillars upon which AI technologies are built. Generative AI and large language models have the ability to create and manipulate human-like content. This power must be wielded responsibly. Data governance requires developers and organizations to embed ethical guidelines within the AI systems themselves, ensuring that these technologies align with society’s values and do not increase biases or the delivery of misinformation. ... Data governance recognizes the importance of individual autonomy in an AI-driven world. It seeks to empower individuals with the ability to exercise control over their own data and determine how it is utilized. By placing decision-making power in the hands of data subjects, we uphold the fundamental principles of self-determination and personal agency.

The Need for Risk-Based Vulnerability Management to Combat Threats

In comparison to traditional and outdated approaches to vulnerability management, a risk-based strategy enables organizations to assess the level of risk posed by vulnerabilities. This approach allows teams to prioritize vulnerabilities based on their assessed risk levels and remediate those with higher risks, minimizing potential attacks in a way that is hassle-free, continuous, and automated. Over 90% of successful cyberattacks involve exploitation of unpatched vulnerabilities and in result the demand for automated patch management solutions is increasing as organization seeking a smarter and more efficient vulnerability remediation strategy than those employed in the past. ... In the face of today’s threats, it is crucial to have actionable insights based on risk that can drive security remediation efforts forward. By continuously assessing your entire attack surface, Outscan NX tools can pinpoint the most pressing threats, saving your security team valuable time and resources. The Outscan NX are a comprehensive suite of internal and external network scanning and cloud security tools customized to suit the unique needs of your organization.

13 go-to podcasts that inspire IT industry leaders today

Risky Business is a weekly cybersecurity news and current events podcast hosted by Patrick Gray and Adam Boileau. I listen to it because they do an excellent job curating the most relevant news and events in cybersecurity that occurred in the previous week. Gray is a journalist with deep cybersecurity knowledge and Boileau is an executive director at a cybersecurity firm, so the presentation is professional and includes insights on threat actors and motivations. ... I find Gartner’s CIO Mind podcast to be especially insightful and relevant to the work I’m doing. It covers a wide range of topics that CIOs are grappling with, from the recession and cost-cutting, to staffing specialized IT roles and employee retention. It keeps me tuned in to what others in the industry care about and what keeps them up at night, and it gets me thinking about ways I can improve my own organization so we can better support our clients. The podcast also shares advice from Gartner analysts and other experts that I can apply to my own organization and leverage to prepare for what’s coming, such as generative AI, workforce trends, research and development investment trends, and more.

IoT brings resource gains, sustainability to agriculture

Long-range, low-power wireless solutions equip farmers with the data they need in order to achieve their goals of increasing yield and minimizing environmental impact. Lacuna Space is expanding Long-Range WAN (LoRaWAN) coverage with satellites and LoRa technology to increase connectivity for low-coverage areas. With the ability to have reliable connectivity despite location, more farmers around the world can gather data that enables them to make informed decisions about irrigation, fertilization and more to improve crop yield and monitor water usage. Farmers in areas without cellular or Wi-Fi signals can now receive the same technological advancements as those in more connected areas. This supports smarter agricultural practices throughout the world, bringing access to tools that improve operations and crop yield to more individuals in the industry. WaterBit, a precision agriculture irrigation company, gives farmers the ability to have real-time, low-cost IoT sensing systems that improve crop quality and yield through optimized resource use.

Risk Assessment Using Blockchain

Blockchain technology promises new ways to conduct risk assessments; it helps to create a distributed, transparent, and tamper-proof system for assessing risks. Not only can this standardize and streamline the process but also improve the accuracy and reliability of results. A point to note is that blockchain can only increase accuracy and make the process more efficient. It cannot replace human judgment and auditing expertise. It can enhance the auditing process by ensuring the integrity of transactions’ and events’ records. ... Decentralized data storage eliminates the chances of a single point of failure, along with reducing the risk of data loss or corruption. One of the key advantages of using blockchain technology is that it allows for decentralized data storage. During risk assessments, information collected can be stored on the blockchain, making it more secure and less vulnerable to attack. Additionally, the distributed nature of blockchain technology means that multiple stakeholders can access and update the data, improving collaboration and ensuring that everyone is working from the same information.

How can organizations maintain data governance when using generative AI?

The key to the reliability and trust of generative AI responses is combining them with cognitive enterprise search technology. As mentioned, this combination generates responses from enterprise data, and users can validate the information source. Each answer is provided in the user’s context, always accounting for data permissions from the data source with full compliance. In addition, these tools ensure data is consistently up-to-date by delta crawling. Integrating generative AI tools into a trusted knowledge management solution allows employees to see which documents their information came from and even provide further explanations.  ... Firstly, leadership must evaluate the potential impact of the generated content on the organization’s reputation, brand image, and the effectiveness it will have on the specific business unit. Legal and ethical implications and ensuring compliance with regulations and guidelines are necessary considerations, just like any other deployed technology.

Responsible tech ecosystems: pragmatic precursors to responsible regulation

Regulatory technology (regtech) is typically two-fold: compliance tech when regulated firms use it and supervisory tech when regulators use it. As regulators monitor and enforce compliance, regtech presents new opportunities to formulate frameworks. For instance, today, AI activities of market firms are governed under disparate regulations such as data protection, consumer protection, financial services regulations etc. However, threats of unfairness, explainability and accountability are yet to be addressed. Regulatory gaps expose unmitigated risks that supervisory technology can resolve. In a perfect world, even without prompts from regtech, organizations should adopt measures to address these gaps and work towards diversity and transparency, which have a direct impact on their AI models. Not every innovation or its ensuing disruption needs to be welcomed. We see this in the raging debate in the AI & Art spaces. Any regulator has the moral obligation to react to emerging technology, even if post-facto. 

Crossing the Data Divide: Closing Gaps in Perception of Data as Corporate Asset

What I am suggesting is that our data leaders need to elevate their vision and messaging to describe a new type of system that is the authoritative reference for all enterprise data assets. This new type of system needs to take its place next to the ERP, CRM, and HRM systems within the enterprise. This means it must provide value for everyone, both technical and non-technical, and also provide context for data assets that include its trustworthiness, source, owner, experts, reviews, and much more, all wrapped in a consumer-grade user interface experience. What is this system? I call it a social data fabric (SDF). That term has been used lightly in the social media world, but I am commandeering it for our purposes. I define an SDF system as a combination of an enterprise data catalog and an internal marketplace where employees can explore and ‘shop’ for data. The catalog portion of the system should ingest and manage a broad number of data, business intelligence, and data-related assets such as term glossaries, KPIs, analytic models, and business processes. 

Executive Q&A: Controlling Cloud Egress Costs

For smaller enterprises, egress charges are fairly minimal as most data resides in a single cloud region and is accessed within that region. For larger enterprises, the number of scenarios which incur egress fees is higher. One such scenario is implementing a hybrid cloud for cost management or a multicloud to make use of the latest optimized computing hardware that might not be available in the primary cloud. For these scenarios, egress fees might be as high as a third of the cloud service expense with naive implementations. More optimal implementations can bring down the egress cost but still fall short as more management complexity is introduced and operations staff needs to be hired to compensate. The reason such fees come as a surprise is that it's hard to predict how much data is going to be accessed across regions, and usually this number only increases with time. ... Moving raw data across network boundaries is infeasible. Building a federation layer to query across all curated data is key. 

Quote for the day:

"Power should be reserved for weightlifting and boats, and leadership really involves responsibility." -- Herb Kelleher

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