Ripe For Disruption: Artificial Intelligence Advances Deeper Into Healthcare
The challenges and changes needed to advance AI go well beyond technology
considerations. “With data and AI entering in healthcare, we are dealing with an
in-depth cultural change, that will not happen overnight,” according to
Pierron-Perlès at her co-authors. “Many organizations are developing their own
acculturation initiatives to develop the data and AI literacy of their resources
in formats that are appealing. AI goes far beyond technical considerations.”
There has been great concern about too much AI de-humanizing healthcare. But,
once carefully considered and planned, may prove to augment human care. “People,
including providers, imagine AI will be cold and calculating without
consideration for patients,” says Garg. “Actually, AI-powered automation for
healthcare operations frees clinicians and others from the menial, manual tasks
that prevent them from focusing all their attention on patient care. While other
AI-based products can predict events, the most impactful are incorporated into
workflows in order to resolve issues and drive action by frontline users.”
Extinguishing IT Team Burnout Through Mindfulness and Unstructured Time
Mindfulness is fundamentally about awareness. For it to grow, begin by
observing your mental state of mind, especially when you find yourself in a
stressful situation. Instead of fighting emotions, observe your mental state
as those negative ones arise. Think about how you’d conduct a deep root cause
analysis on an incident and apply that same rigor to yourself. The key to
mindfulness is paying attention to your reaction to events without judgment.
This can unlock a new way of thinking because it accepts your reaction, while
still enabling you to do what is required for the job. This contrasts being
stuck behind frustration or avoiding new work as it rolls in. ... Mindfulness
is an individual pursuit, while creativity is an enterprise pursuit, and
providing space for employees to be creative is another key to preventing
burnout. But there are other benefits as well. There is a direct correlation
between creativity and productivity. Teams that spend all their time working
on specific processes and problems struggle to develop creative solutions that
could move a company forward.
Overcoming the Four Biggest Barriers to Machine Learning Adoption
The first hurdles with adopting AI and ML are experienced by certain
businesses even before they begin. Machine learning is a vast field that
pervades most aspects of AI. It paves the way for a wide range of potential
applications, from advanced data analytics and computer vision to Natural
Language Processing (NLP) and Intelligent Process Automation (IPA). A general
rule of thumb for selecting a suitable ML use case is to “follow the money” in
addition to the usual recommendations on framing the business goals – what
companies expect Machine Learning to do for their business, like improving
products or services, improving operational efficiency, and mitigating risk.
... The biggest obstacle to deploying AI-related technologies is corporate
culture. Top management is often reluctant to take investment risks, and
employees worry about losing their jobs. Businesses must start with
small-scale ML use cases that demand realistic investments to achieve quick
wins and persuade executives in order to assure stakeholder and employee
buy-in. By providing workshops, corporate training, and other incentives, they
can promote innovation and digital literacy.
Fixing Metadata’s Bad Definition
A bad definition has practical implications. It makes misunderstandings much
more likely, which can infect important processes such as data governance and
data modeling. Thinking about this became an annoying itch that I couldn’t
scratch. What follows is my thought process working toward a better
understanding of metadata and its role in today’s data landscape. The problem
starts with language. Our lexicon hasn’t kept up with modern data’s complexity
and nuance. There are three main issues with our current discourse about
metadata: Vague language - We talk about data in terms of “data” or
“metadata”. But one category encompasses the other, which makes it very
difficult to differentiate between them. These broad, self-referencing terms
leave the door open to being interpreted differently by different people. A
gap in data taxonomy - We don’t have a name for the category of data that
metadata describes, which creates a gap at the top of our data taxonomy. We
need to fill it with a name for the data that metadata refers to. Metadata is
contextual - The same data set can be both metadata and not metadata depending
on the context. So we need to treat metadata as a role that data can play
rather than a fixed category.
Addressing Privacy Challenges in Retail Media Networks
The top reason that consumers cite for mistrusting how companies handle their
data is a lack of transparency. Customers know at this point that companies
are collecting their data. And many of these customers won’t mind that you’re
doing it, as long as you’re upfront about your intentions and give them a
clear choice about whether they consent to have their data collected and
shared. What’s more, recent privacy laws have increased the need for companies
to shore up data security or face the consequences. In the European Union,
there’s the General Data Protection Regulation (GDPR). In the U.S., laws vary
by state, but California currently has the most restrictive policies thanks to
the California Consumer Protection Act (CCPA). Companies that have run afoul
of these laws have incurred fines as big as $800 million. Clearly, online
retailers that already have — or are considering implementing — a retail media
network should take notice and reduce their reliance on third-party data
sources that may cause trouble from a compliance standpoint.
For Gaming Companies, Cybersecurity Has Become a Major Value Proposition
Like any other vertical industry, games companies are tasked with protecting
their organizations from all nature of cybersecurity threats to their
business. Many of them are large enterprises with the same concerns for the
protection of internal systems, financial platforms, and employee endpoints as
any other firm. "Gaming companies have the same responsibility as any other
organization to protect customer privacy and preserve shareholder value. While
not specifically regulated like hospitals or critical infrastructure, they
must comply with laws like GDPR and CaCPA," explains Craig Burland, CISO for
Inversion6, a managed security service provider and fractional CISO firm.
"Threats to gaming companies also follow similar trends seen in other segments
of the economy — intellectual property (IP) theft, credential theft, and
ransomware." IP issues are heightened for these firms, like many in the
broader entertainment category, as content leaks for highly anticipated new
games or updates can give a brand a black eye at best, and at worst hit them
more directly in the financials.
Driving value from data lake and warehouse modernisation
To achieve this, Data Lakes and Data Warehouses need to grow alongside the
business requirements in order to be kept efficient and up to date. Go
Reply is a leading Google Cloud Platform Service integrator (SI) that is
helping companies that span multiple sectors along this vital journey.
Part of the Reply Group, Go Reply is a Google Cloud Premier Partner focussing
on areas to include Cloud Strategy and Migration; Big Data; Machine Learning;
and Compliance. With Data Modernisation capabilities in the GCP environment
constantly evolving, businesses can become overwhelmed and unsure on not only
next steps, but more importantly next steps for them, particularly if they
don’t have in-house Google expertise. Companies often need to utilise both
Data Lakes and Data Warehouses simultaneously so guidance on how to do this,
as well as driving value from both kinds of storage is vital. When speaking to
the Go Reply leadership team they advise that Google Cloud Platform being
the hyperscale cloud of choice for these workloads, brings technology around
Data Lake, and Data Warehouse efficiency, along with security superior to
other market offerings.
Three tech trends on the verge of a breakthrough in 2023
The second big trend is around virtual reality, augmented reality and the
metaverse. Big tech has been spending big here, and there are some suggestions
that the basic technology is reaching a tipping point, even if the broader
metaverse business models are, at best, still in flux. Headset technologies
are starting to coalesce and the software is getting easier to use. But the
biggest issue is that consumer interest and trust is still low, if only
because the science fiction writers got there long ago with their dystopian
view of a headset future. Building that consumer trust and explaining why
people might want to engage is just as a high a priority as the technology
itself. One technology trend that's perhaps closer, even though we can't see
it, is ambient computing. The concept has been around for decades: the idea is
that we don't need to carry tech with us because the intelligence is built
into the world around us, from smart speakers to smart homes. Ambient
computing is designed to vanish into the environment around us – which is
perhaps why it's a trend that has remained invisible to many, at least until
now.
CIOs beware: IT teams are changing
The role of IT is shifting to be more strategy-oriented, innovative, and
proactive. No longer can days be spent responding to issues – instead, issues
must be addressed before they impact employees, and solutions should be
developed to ensure they don’t return. What does this look like? Rather than
waiting for an employee to flag an issue within their system – such as
recurring issues with connectivity, slow computer start time, etc. – IT can
identify potential threats to workflows before they happen. They plug the
holes, then they establish a strategy and framework to avoid the problem
entirely in the future. In short, IT plays a critical role in successful
workplace flow in both a proactive and reactive way. For those looking to
start a career in IT, the onus falls on them to make suggestions and changes
that look holistically at the organization and how employees interact within
it. IT teams are making themselves strategic assets by thinking through how to
make things more efficient and cost-effective in the long term.
A Comprehensive List of Agile Methodologies and How They Work
Extreme Programming (or XP), offers some of the best buffers against
unexpected changes or late-stage customer demands. Within sprints and from the
start of the business process development, feedback gathering takes place.
It’s this feedback that informs everything. This means the entire team becomes
accustomed to a culture of pivoting on real-world client demands and outcomes
that would otherwise threaten to derail a project and seriously warp lead time
production. Any organization with a client-based focus will understand the
tightrope that can exist between external demands and internal resources.
Continuously orienting those resources based on external demands as they
appear is the single most efficient way to achieve harmony. This is something
that XP does organically once integrated into your development culture. ,,.
Trimming the fat from the development process is what this method is all
about. If something doesn’t add immediate value, or tasks within tasks seem to
be piling up, the laser focus of Lean Development steps in.
Quote for the day:
"Confident and courageous leaders have
no problems pointing out their own weaknesses and ignorance. " --
Thom S. Rainer
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