Daily Tech Digest - May 10, 2024

Optimize AI at Scale With Platform Engineering for MLOps

Just as platform engineering emerged from the DevOps movement to streamline app development workflows, so too must platform engineering streamline the workflows of MLOps. To achieve this, one must first recognize the fundamental differences between DevOps and MLOps. Only then can one produce an effective platform engineering solution for ML engineers. To enable AI at scale, enterprises must commit to developing, deploying and maintaining platform engineering solutions that are purpose-built for MLOps. Whether due to data governance requirements or practical concerns about moving vast volumes of data over significant geographical distances, MLOps at scale require enterprises to utilize a spoke-and-wheel approach. Model development and training occurs centrally, trained models are distributed to edge locations for fine-tuning on local data, and fined-tuned models are deployed close to where end users interact with them and the AI applications they leverage. ... Enterprises should hire engineers with MLOps experience to fill platform engineering roles appropriately. According to research from the World Economic Forum, AI is projected to create around 97 million new jobs by 2025. 

The Blockchain Integrity Act: Latest Attempt to Restrict Financial Privacy

In short, the Blockchain Integrity Act would first establish a two‐​year moratorium that prohibits financial institutions from going anywhere near cryptocurrency that has been routed through a mixer. With that two‐​year moratorium in place, the Blockchain Integrity Act would then require the Department of the Treasury to study how people use mixers and other privacy‐​enhancing technology. ... The second half of the legislation—the request for a study—is less concerning if it’s considered alone and without the surrounding context. The request seeks information regarding different types of privacy‐​enhancing technology, illicit and legitimate use history, and an analysis of what the government’s role might be here. Those are all reasonable inquiries. Again, without additional context, it’s an encouraging sign that Representative Casten is interested in learning more about how this technology is used for both better and worse. Yet what isn’t encouraging is that Representative Casten introduced the bill saying that “until we’ve studied [privacy enhancing technologies like mixers] and have a good audit trail, the presumption should be that these are money laundering channels.”

Some strategies for CISOs freaked out by the specter of federal indictments

“Some CISOs feel like they’re the frog that’s in the water that’s starting to boil, and they don’t like that feeling, and they want to make sure that they’re doing the right things to navigate that heat,” Sullivan said during a panel discussion, “CISOs Under Indictment: Case Studies, Lessons Learned, and What’s Next,” at this year’s RSA Conference. The panel of current and former CISOs emphasized that in this environment, CISOs need to document their roles and responsibilities, involve the right people in incident response and decision-making processes, and have the courage to stand up for their convictions to minimize the risk that they will face the same fates as Sullivan and Brown. ... “The heat is up because the reality is you’ve got these entities in government who are responding to a huge rise in cybercrime in a way that no one can hide. It’s not like in the old days when if an incident happened, most people wouldn’t notice when stuff happens. Today, the whole world notices,” he said. Blauner’s bottom-line advice to CISOs to protect themselves is to “take a look at every governance document you’ve got and really make sure that it’s crystal clear about roles and responsibilities, especially around who makes risk management decisions.”

Wearable devices can now harvest our brain data. Australia needs urgent privacy reforms

In a background paper published earlier this year, the Australian Human Rights Commission identified several risks to human rights that neurotechnology may pose, including rights to privacy and non-discrimination. Legal scholars, policymakers, lawmakers and the public need to pay serious attention to the issue. The extent to which tech companies can harvest cognitive and neural data is particularly concerning when that data comes from children. This is because children fall outside of the protection provided by Australia’s privacy legislation, as it doesn’t specify an age when a person can make their own privacy decisions. The government and relevant industry associations should conduct a candid inquiry to investigate the extent to which neurotechnology companies collect and retain this data from children in Australia. The private data collected through such devices is also increasingly fed into AI algorithms, raising additional concerns. These algorithms rely on machine learning, which can manipulate datasets in ways unlikely to align with any consent given by a user.

Cloud environments beyond the Big Three

The resurgence and innovation in edge computing and on-premises technology further support the trend toward diversification as data generation and consumption locations continue to spread geographically. ... Edge computing addresses these limitations by processing data closer to where it is generated. This drastically reduces latency and enhances the user experience in applications such as IoT, retail tech, and smart manufacturing. Although many consider edge computing to be small devices, it also includes entire data centers and smaller server installations that exist to serve a specific business location. Many enterprises don’t see the wisdom of sending their data on a 2,000-mile round trip to the point of presence for a public cloud provider, which happens more often than we understand. Additionally, although the cloud offers good scalability and flexibility, concerns over data sovereignty and security continue to push certain industries towards on-premises solutions. Sensitive data and critical applications in sectors such as finance, government, and healthcare often necessitate keeping data in-house under strict regulatory frameworks.

Controlling chaos using edge computing hardware: Digital twin models promise advances in computing

Using machine learning tools to create a digital twin (a virtual copy) of an electronic circuit that exhibits chaotic behavior, researchers found that they were successful at predicting how it would behave and at using that information to control it. Many everyday devices, like thermostats and cruise control, utilize linear controllers—which use simple rules to direct a system to a desired value. Thermostats, for example, employ such rules to determine how much to heat or cool a space based on the difference between the current and desired temperatures. Yet because of how straightforward these algorithms are, they struggle to control systems that display complex behavior, like chaos. As a result, advanced devices like self-driving cars and aircraft often rely on machine learning-based controllers, which use intricate networks to learn the optimal control algorithm needed to operate efficiently. However, these algorithms have significant drawbacks, the most demanding of which is that they can be extremely challenging and computationally expensive to implement.

Digital recreations of dead people need urgent regulation, AI ethicists say

Such services, which are already technically possible to create and legally permissible, could let users upload their conversations with dead relatives to “bring grandma back to life” in the form of a chatbot, researchers from the University of Cambridge suggest. They may be marketed at parents with terminal diseases who want to leave something behind for their child to interact with, or simply sold to still-healthy people who want to catalogue their entire life and create an interactive legacy. But in each case, unscrupulous companies and thoughtless business practices could cause lasting psychological harm and fundamentally disrespect the rights of the deceased, the paper argues. “Rapid advancements in generative AI mean that nearly anyone with internet access and some basic knowhow can revive a deceased loved one,” said Dr Katarzyna Nowaczyk-BasiƄska, one of the study’s co-authors at Cambridge’s Leverhulme centre for the future of intelligence (LCFI). “This area of AI is an ethical minefield. It’s important to prioritise the dignity of the deceased, and ensure that this isn’t encroached on by financial motives of digital afterlife services, for example.”

How To Take The A-I-M Approach To Leadership

I like to break down the concept of taking aim into three components, which I call the A-I-M approach: appreciation, imagination and motivation. The common thread across all three of these principles is communication—and leaders cannot be effective without it. Showing genuine gratitude is a foundational aspect of effective leadership. Expressing heartfelt encouragement demonstrates empathy and humility. And this simple show of appreciation directly benefits the organization by motivating employees to continue contributing to the company’s success and nurturing their loyalty. ... A leader’s job is not to be the author of all ideas but to inspire team members to tap into their imaginations and present fresh approaches to solving problems, delivering solutions and communicating with clients.  ... One of the responsibilities of a leader is to understand what moves their teams into action. As author and leadership coach John Maxwell famously wrote, “A leader is great not because of his or her power, but because of his or her ability to empower others.” I call that motivation.

Colorado AI legislation further complicates compliance equation

CIOs might struggle with the bill’s language because the focus is on whether AI — in any form — helps make “consequential decisions” that could impact Colorado residents. The bill defines consequential decision as being any decision “that has a material legal or similarly significant effect on the provision or denial to any consumer,” which includes educational enrollment, employment or employment opportunity, financial or lending service, healthcare services, housing, insurance, or a legal service. ... Another provision could prove onerous for CIOs who do not have full knowledge of every AI implementation in use in their environment, as it requires companies to make “a publicly available statement summarizing the types of high-risk systems that the deployer currently deploys, how the deployer manages any known or reasonably foreseeable risks of algorithmic discrimination that may arise from deployment of each of these high-risk systems and the nature, source, and extent of the information collected and used.” ... One especially dicey area in the legislation that should concern CIOs is when AI — especially generative AI — acts on its own. 

AI's Game-Changing Role in Finance and Audit Processes

Auditors can face several risks when using AI. These risks include over-reliance on AI-generated insights, potential biases and quality issues from incomplete or poor-quality data andcybersecurity threats such as consequences in terms of hacking of the confidential data from the AI websites. Thus, it is necessary to ensure compliance and implement safeguarding measures. Following are some of the possible measures that can be implemented to mitigate the above-mentioned risks. Human judgement: While AI is a great tool to be incorporated in the professional world to help auditors and organisations streamline their existing processes, AI work on standard algorithm that can’t be customised on case-to-case basis. Therefore, to ensure the accuracy of the results, a human review can be placed in practice to review from and validate the accuracy of output results. Updating back-end algorithms: The better the algorithms, the better the results. Regular updates to the back-end algorithms can yield more accurate and improved outputs, adapting to changing scenarios and data formats, ultimately mitigating the risk of incorrect or inaccurate results..

Quote for the day:

"Don't find fault, find a remedy." -- Henry Ford

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