Together For Good: How Humans And AI Can Close The Health Gap
While the potential is immense, AI’s effectiveness in closing the health gap hinges on more than just technological advancement. AI must be deliberately tailored, trained, tested, and targeted to bring out the best in and for people and the planet. This means anchoring AI development and deployment in a holistic understanding of humans, and the environment they evolve in. It also entails the design of ethical frameworks, transdisciplinary collaboration, and 360-degree strategies that systematically bring out the complementarity of AI and NI, including the knowledge, experience, and intuition of humans. ... Closing the gap of preventable health inequalities cannot be achieved by advanced algorithms alone. It requires us to integrate the strengths of artificial intelligence with natural intelligence — the knowledge, ethical judgment, empathy, and cultural understanding of human beings — to ensure that solutions are both effective and just. By anchoring AI in localized insight and human expertise, we can align personal health improvements (micro) with community-led action (meso), informed national policies (macro), and globally coordinated strategies (meta), delivering equitable outcomes in every arena of the organically evolving kaleidoscope that we are part of.
How to Take a Security-First Approach to AI Implementation
Whether it's a third-party tool or an in-house project, thorough research and a
clear plan will go a long way toward reducing risks. When developing guidelines
for AI implementation, the first step is to match the business case with
available tools, remembering that some models are more suited to specific tasks
than others. Practicing a Secure by Design strategy from the ground up can
future-proof AI implementation. These principles ensure that security is
prioritized throughout the entire lifecycle of an AI product. A Secure by Design
methodology implements multiple layers of defense against cyberthreats. During
the planning stage, the security team's input is critical for a Secure by Design
approach. Vendor trust is also vital. Evaluating vendors for trustworthiness and
auditing contracts thoroughly, including regular monitoring of updates to vendor
terms and conditions, are imperative. It is essential for data quality to be
assessed for metrics like accuracy, relevance, and completeness.... Keeping
security at the forefront from the get-go confers advantages, especially as
tools and risks evolve. Safer AI is on the horizon as more users adhere to best
practices through regulatory frameworks, international collaborations, and
security-first use cases.
Data Governance in DevOps: Ensuring Compliance in the AI Era
Implementing effective CI/CD pipeline governance in the age of AI requires a
multifaceted approach. It starts with establishing clear policies outlining
compliance requirements, security standards, and ethical guidelines for AI
development. These policies should be embedded into the pipeline through
automated checks and gates. Leveraging advanced automation tools for
continuous compliance checking throughout the pipeline is essential. These
tools can scan code for vulnerabilities, check for adherence to coding
standards, and even analyze AI models for potential biases or unexpected
behaviors. Robust version control and change management processes are also
crucial components of pipeline governance. They ensure that every change to
the codebase or AI model is tracked, reviewed, and approved before progressing
through the pipeline. We can't forget logging and auditing. Comprehensive
logging and monitoring of all pipeline activities provide the necessary audit
trails for compliance demonstration and post-incident analysis. In the context
of AI, this extends to monitoring deployed models for performance drift or
unexpected behaviors, ensuring ongoing compliance post-deployment.
Top 10 Cloud Data Center Stories of 2024
If you work in the data center industry, you may use term on-premise (or
on-prem) frequently. But have you ever stopped to wonder how the phrase
entered the data center lexicon – or considered why on-premise doesn’t make
grammatical sense? In a nutshell, the answer is that it should be on-premises
– note the s on the end – because premise and premises are different words. If
not, you’ll be enlightened by our coverage of the history of the term on-prem
and why it has long irked certain CIOs. ... The more complex your cloud
architecture becomes, the harder it is to identify security risks and other
misconfigurations. That’s why the ability to automate security assessments is
growing increasingly important. But how good are the solutions that cloud
providers offer for this purpose? To find out, we took a close look at
compliance reporting tools from Azure and GCP. The takeaway was that these
solutions can automate much of the work necessary to identify
misconfigurations that could trigger compliance violations, but they’re no
substitute for human experts. ... What was less often discussed – but equally
important – is the role of edge infrastructure in AI. That’s what we focused
on in our report about edge AI, meaning AI workloads that run at the network
edge instead of in traditional cloud data centers.
Clop Ransomware Takes Responsibility for Cleo Mass Exploits
Whether or not Clop is actually responsible for attacks targeting various
types of Cleo's MFT software couldn't be confirmed. Separately, on Dec. 10,
British cybersecurity expert Kevin Beaumont reported having evidence that the
ransomware group Termite possessed a zero-day exploit for vulnerabilities in
the Cleo products. Security experts said both groups may well have been
involved, either separately or together. "Although Cl0p posted a message on
their website, this is not hard evidence pointing to a single threat group's
involvement. Therefore, any discussion of whether Termite or Cl0p are behind
this exploit is speculation until proven with other indicators/evidence," said
Christiaan Beek, senior director of threat analytics at cybersecurity firm
Rapid7. "We have seen Cl0p utilize complex chains similar to this
vulnerability in multiple file transfer use cases before, such as MOVEit and
Accellion FTA in 2021," Beek added. ... The latest attacks appear to
target in part CVE-2024-50623, an unrestricted file upload vulnerability in
the managed file transfer products Cleo Harmony, VLTrader and LexiCom.
Exploiting the vulnerability enables attackers to remotely execute code with
escalated privileges.
Balancing security and user experience to improve fraud prevention strategies
There may not be one right way of handling the balance of security and
user-friendly customer experience. Different institutions and their customers
will have different needs, and processes might vary somewhat. But overall,
there should be clear, easy-to-follow standards and checkpoints built into
whatever financial institutions do. For instance, some banks or credit card
companies may allow customers to institute their own stop gap for purchases
over a certain amount, which may reduce the incentive for relatively
large-scale fraud. These companies could also introduce some level of
personalization into the processes, like how a credit or debit card could be
easily turned on and turned off by customers themselves via an app or site.
... Meanwhile, it seems like barely a day goes by when there’s not some
coverage of fraud or a release of personal info via hacking from some
corporation, and some speculate increasingly advanced technology may make it
easier for those who want to perpetrate fraud. With this in mind, there may be
a greater emphasis placed on enhancing security and experimentation in what
different institutions do to find what works best and to have a process in
place that allows customers to have confidence in their banks and credit card
companies.
Generative AI Is Just the Beginning — Here’s Why Autonomous AI is Next
Embracing this technology will unlock significant opportunities to improve
organizational efficiency and accuracy. But before we dive into this, let us
start with some definitions. Autonomous AI refers to systems that can perform
tasks without human intervention. In contrast, generative AI systems focus on
content creation based on existing data. What sets autonomous AI apart is its
ability to self-manage. Understanding this difference is crucial, enabling
organizations to use AI for more complex operations like predictive
maintenance and resource optimization. ... The first step in successfully
integrating autonomous AI into your organization is implementing robust data
governance frameworks to support these advanced systems. Establish clear data
privacy and transparency guidelines to ensure autonomous AI operates within
ethical boundaries. It’s crucial to incorporate technical controls that
prevent the AI from making reckless decisions, aligning its actions with your
organizational values. ... When exploring the future of autonomous AI within
your organization, it’s crucial to monitor and evaluate your autonomous AI
systems regularly. Continuous assessment allows you to understand how the AI
is performing and identify potential improvement areas.
Privacy by design approach drives business success in today’s digital age
Businesses that adhere to data privacy practices validate the upkeep of
customer data and data privacy, earning them a stronger brand reputation. They
should also ensure privacy is embedded in the organisation’s framework across
the technology, products, and services, which is also known as Privacy by
Design (PbD). ... The PbD framework was developed by Dr. Ann Cavoukian,
Information & Privacy Commissioner of Ontario jointly with the Dutch Data
Protection Authority and the Netherlands Organisation for Applied Scientific
Research in 1995. It aimed to cultivate and embed privacy defences to
safeguard data in the design process of a product, service, or system. Privacy
becomes the default setting built at the very beginning rather than an
afterthought. This framework is founded on seven core principles: being
proactive and not reactive, having privacy as the default setting, having
privacy embedded into design, full functionality, end-to-end security,
visibility and transparency, and respect for user privacy. ... The PbD
approach which is proactive indicates the company’s commitment to protecting
the customer’s sensitive personal information. PbD enables companies to have
personalised engagement with customers while respecting their privacy
preferences.
Top 10 cybersecurity misconfigurations: Nail the setup to avoid attacks
Despite the industry-wide buzz about things like zero-trust, which is rooted
in concepts such as least-privileged access control, this weakness still runs
rampant. CISA’s publication calls out excessive account privileges, elevated
service accounts, and non-essential use of elevated accounts. Anyone who has
worked in IT or cyber for some time knows that many of these issues can be
traced back to human behavior and the general demands of working in complex
environments. ... Another fundamental security control that makes an
appearance is the need to segment networks, a practice again that ties to the
broader push for zero trust. By failing to segment networks, organizations are
failing to establish security boundaries between different systems,
environments, and data types. This allows malicious actors to compromise a
single system and move freely across systems without encountering friction and
additional security controls and boundaries that could impede their nefarious
activities. The publication specifically calls out challenges where there is a
lack of segmentation between IT and OT networks, putting OT networks at risk,
which have real-world implications around security and safety in environments
such as industrial control systems.
Why Indian enterprises are betting big on hybrid multi-cloud strategies?
The multi-cloud strategy in India is deeply intertwined with the country’s
broader digital transformation initiatives. The Government of India’s Digital
India program and initiatives like the National Cloud Initiatives are
providing a robust framework for cloud adoption. ... The importance of edge
computing is growing, and the rollout of 5G is opening up new possibilities
for distributed cloud architectures. Telecom titans like Jio and Airtel are
investing substantially in cloud-native infrastructure, creating ripple
effects throughout industries. On the other hand, startup ecosystems play a
crucial role too. Bangalore, often called the Silicon Valley of India, has
become a hotbed for cloud-native technologies. Companies and numerous cloud
consulting firms are developing cutting-edge multi-cloud solutions that are
gaining global recognition. Foreign investments are pouring in. Major cloud
providers like AWS, Microsoft Azure, and Google Cloud are expanding their
infrastructure in India, with dedicated data centers that meet local
compliance requirements. This local presence is critical for enterprises
concerned about data sovereignty and latency.
Quote for the day:
"You aren’t going to find anybody
that’s going to be successful without making a sacrifice and without
perseverance." -- Lou Holtz
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