The ICO said Clearview violated several tenets of UK data protection law, including failing to use data in a way that is “fair and transparent” (given that residents’ images were scraped without their knowledge or consent), “failing to have a lawful reason for collecting people’s information,” and “failing to have a process in place to stop the data being retained indefinitely.” However, although ICO has issued a fine against Clearview and ordered the company to delete UK data, it’s unclear how this might be enforced if Clearview has no business or customers in the country to sanction. In response to a similar deletion order and fine issued in Italy under EU law earlier this year, Clearview’s CEO Hoan Ton-That responded that the US-based company was simply not subject to EU legislation. ... In response to the same query, Lee Wolosky of Jenner and Block, Clearview’s legal representatives, told The Verge: “While we appreciate the ICO’s desire to reduce their monetary penalty on Clearview AI, we nevertheless stand by our position that the decision to impose any fine is incorrect as a matter of law ... ”
On the one hand, AI authors don’t copy anything into the algorithm. On the other hand, the neural network is incapable of independent thinking. All the code it produces is a combination of fragments it has seen during the learning phase. It may even create pieces of code that look like exact copies from the training dataset. The point is that even pieces that look independent are no more independent than the copies. The problem is pretty new, and we haven’t seen any court decisions yet. This uncertainty slows down the progress of product developers: people don’t want to make significant investments into something that might become illegal tomorrow. We faced the same issue when creating our code completion system. In addition to the potential legal limitations, there were technical difficulties as well. The code we can find in an open-source repository is in some sense “complete”. It usually compiles, passes simple tests, has clear formatting, doesn’t contain duplicate blocks or temporary debug sections. However, the code we have to work with in the editor is not “complete” most of the time.
From a programming perspective, the ORM layer is an adapter layer: it adapts the language of object graphs to the language of SQL and relational tables. The ORM layer allows object-oriented developers to build software that persists data without ever leaving the object-oriented paradigm. When you use JPA, you create a map from the datastore to your application's data model objects. Instead of defining how objects are saved and retrieved, you define the mapping between objects and your database, then invoke JPA to persist them. If you're using a relational database, much of the actual connection between your application code and the database will then be handled by JDBC. As a specification, JPA provides metadata annotations, which you use to define the mapping between objects and the database. Each JPA implementation provides its own engine for JPA annotations. The JPA spec also provides the PersistanceManager or EntityManager, which are the key points of contact with the JPA system
Unlike Google Glass, the translation-glasses prototype is augmented reality (AR), too. Let me explain what I mean. Augmented reality happens when a device captures data from the world and, based on its recognition of what that data means, adds information to it that’s available to the user. Google Glass was not augmented reality — it was a heads-up display. The only contextual or environmental awareness it could deal with was location. Based on location, it could give turn-by-turn directions or location-based reminders. But it couldn’t normally harvest visual or audio data, then return to the user information about what they were seeing or hearing. Google’s translation glasses are, in fact, AR by essentially taking audio data from the environment and returning to the user a transcript of what’s being said in the language of choice. Audience members and the tech press reported on the translation function as the exclusive application for these glasses without any analytical or critical exploration, as far as I could tell. The most glaring fact that should have been mentioned in every report is that translation is just an arbitrary choice for processing audio data in the cloud.
With AR headsets and new techniques for registering 3D medical images to a patient’s real body, the superpower of x-ray vision is now a reality. In an impressive study from Teikyo University School of Medicine in Japan, an experimental emergency room was tested with the ability to capture whole-body CT scans of trauma patients and immediately allow the medical team, all wearing AR headsets, to peer into the patient on the exam table and see the trauma in the exact location where it resides. This allowed the team to discuss the injuries and plan treatment without needing to refer back and forth to flat screens, saving time, reducing distraction, and eliminating the need for mental transformations. In other words, AR technology takes medical images off the screen and places them in 3D space at the exact location where it’s most useful to doctors – perfectly aligned with the patient’s body. Such a capability is so natural and intuitive, that I predict it will be rapidly adopted across medical applications. In fact, I expect that in the early 2030s doctors will look back at the old way of doing things, glancing back and forth at flat screens, as awkward and primitive.
It turns out the combination of the URL on the image and my reply gave them enough information to take over my account. Now, even when I saw trouble brewing -- an Instagram e-mail came asking me if I wanted to change my phone number to one in Nigeria -- I wasn't too worried. I'd protected my account with two-factor authentication (2FA). While 2FA isn't perfect, it's better than anything else out there for basic security. But, here's where things went awry. Instagram should have sent me an e-mail with a link asking me to "revert this change." Instagram didn't send such a message. Instead, I received e-mails from email@example.com that provided a link about how to "secure your account." This dropped me into Instagram's pages for a hacked account, which wasn't any help. ... Argh! I followed up with Instagram's suggestions on how to bring my account back. I asked for a login link from my Android Instagram app. I got one, which didn't work. Next, I requested a security code. I got one. That didn't work either, no doubt because -- by that time -- the account was now responding to its "new" e-mail address and phone number.
“The recurring theme with Gen. Z — beside the compensation piece — is the focus on workplace flexibility and mental health. Those are two places we see a huge divergence form other generations,” Remley said. “If we’d talk to Boomers or Gen Xers concerning mental health benefits, they would say that’s my business and not my employer’s business. Whereas, Gen Z is wanting assistance with mental health from their employers.” Benefits ranked high in both surveys as reasons workers are drawn to and want to remain with an organization. At the top of the list: good mental healthcare and healthcare benefits in general. And, employers do seem to be making progress when it comes to prioritizing mental health and well-being in the workplace, Deloitte reported. "More than half agree that workplace well-being and mental health has become more of a focus for their employers since the start of the pandemic. However, there are mixed reviews on whether the increased focus is actually having a positive impact," Deloitte's report stated.
Innovating for sustainability will continue to be a key focus for us and our customers, and we are committed to finding new ways to help them on their journeys to net zero in any way we can. Not only does focusing on sustainability ensure business continuity by conserving resources but customers and employees want to buy from and work for companies that share their values. We believe sustainability is a shared responsibility and we want to set a strong example. Through our beGreen program, we provide coworkers with the platform to share ideas and take collective action to improve our environment. Areas of focus include coworker education, community awareness, recycling and resource conservation. The program is managed by a cross-functional team of coworkers from multiple CDW locations. This team collaborates internally and with members of the communities where we operate. Sustainability can no longer be a secondary consideration, which is why we’re also in the process of developing a global plan to make realistic, attainable and strong commitments to being a more sustainable organisation ourselves, while working with our partners and customers to do the same.
IDaaS isn’t all sunshine and rainbows though, and organizations much account for some major considerations when evaluating it. If identity is truly the new perimeter, adopting IDaaS gives some level of control of your perimeter to an IDaaS service provider. This is similar to the shared responsibility model concept in cloud computing but extended further up the stack from not just infrastructure but to critical things such as identities, permissions, and access control. Some of the benefits cited in the above table can now potentially be a vice or point of contention depending on your organizational requirements and security sensitivity. Since you are consuming the application and system associated with IAM, you now are limited to the permissions the providers offering includes and likely have limited ability to alter the way the offering functions. This is due to the reality that the IDaaS provider offers their interface/application to many customers and can only have so much customization without losing the ability to have a standardized offering.
The first element is an AI model, which uses both internal and external data to assess competencies against a core skill set we are seeking to assess and develop; e.g., a full-stack engineer. It compares employees’ skill sets to someone in a similar role or title in the external marketplace on a scale of 1 to 5. We also pull in internal data sources, such as Jira and Workday, which contain information from their resumes, for example. That helps strengthen the accuracy and correlation of the model. The second element used to assess skill sets is an employee self-assessment. Employees receive the results of the AI model, and they validate whether they believe their skills are in line with the AI assessment. The final prong is the manager assessment, in which the manager rates the skills of that individual employee. This approach to assessing skill sets has been valuable for several reasons. First, it ensures the use of objective information in the evaluation process, reducing the influence of subjective views that managers may have, based on limited interactions with employees.
Quote for the day:
"One of the sad truths about leadership is that, the higher up the ladder you travel, the less you know." -- Margaret Heffernan