Despite recent progress, AI-powered chatbots still have a long way to go
Even state-of-the-art systems struggle to have a human-like conversation without
tripping up, clearly. But as these systems improve, questions are arising about
what the experience should ultimately look like. Values, dialects, and social
norms vary across cultures, ethnicities, races, and even sexual identities,
presenting a major challenge in designing a chatbot that works well for all
potential users. An ostensibly “safe,” polite, and agreeable chatbot might be
perceived as overly accommodating to one person but exclusionary to another.
Another unsolved problem is how chatbots should treat controversial topics like
religion, illegal activities, conspiracy theories, and politics — or whether
they should opine about these at all. A recent paper coauthored by researchers
at Meta explores the potential harm that might arise from chatbots that give
poor advice, particularly in the medical or psychological realms. In a prime
example, OpenAI’s GPT-3 language model can be prompted to tell a person to
commit suicide.
Four emerging data integration trends to assess
Modern data integration technologies focus on advanced automation, connected
data intelligence and persona-based interactive tooling, helping organisations
to accelerate various use cases and other data integration requirements.
Distributed hybrid and multicloud data is creating new integration challenges.
Data lives everywhere, so centralising it into data lakes or data hubs to
support business insights is no longer practical, especially with the explosion
of data at the edge. Forrester expects the adoption of data integration systems
to proliferate in the coming years as organisations look for supporting insights
across multicloud, hybrid cloud and edge environments. Artificial
intelligence (AI) is driving the next level of data integration solutions. New
and innovative AI features are helping enterprises to automate data integration
functions, including data ingestion, classification, processing, security and
transformation. Although AI capabilities within data integration are still
emerging, areas that technology architecture and delivery leaders can leverage
today include the ability to discover connected data, classify and categorise
sensitive data, identify duplicates and orchestrate silos.
Engineering EDA and microservices applications for performance
Microservices application architecture is taking root across the enterprise
ecosystem. Organizing and efficiently operating microservices in multicloud
environments and making their data available in near-real time are some of the
key challenges enterprise architects confront with this design. Thanks to
developments in event-driven architecture (EDA) platforms (such as Apache
Kafka) and data-management techniques (such as data mesh and data fabrics),
designing microservices-based applications has become much easier. However, to
ensure that microservices-based applications perform at requisite levels, you
must consider critical non-functional requirements (NFRs) in the design. NFRs
address how a system operates, rather than how the system functions (the
functional requirements). The most important NFRs involve performance,
resiliency, availability, scalability, and security. This article describes
designing for performance, which entails low-latency processing of events and
high throughput. Future articles will address the other NFRs.
12 CISO resolutions for 2022
“It’s important for our security teams to have visibility into all aspects
of cloud applications, on-prem applications, network, services, systems,
databases, accounts, third-party providers, etc. to help fortify our
cybersecurity defenses,” Karki explains. “Having a complete, accurate and
appropriately prioritized inventory of all our hardware, software, and
supply chain assets enables our security teams to take a systematic approach
to knowing what needs to be safeguarded, what controls to implement to
protect, defend, and respond against any adverse events, and how to identify
and produce metrics that tell the full story about our current security
posture.” ... Although the complexity of that mesh has been growing for
years, Van Horenbeeck says events during the past two years such as
SolarWinds and Log4j have reinforced for him the criticality of
understanding all the moving parts that make up his company’s technology
ecosystem. To that end, Van Horenbeeck has invested in technology to gain a
fuller understanding of his own company’s IT environment.
New kids on the blockchain - or more of the same old?
Blockchain and Distributed Ledger Technology (DLT) have been on a downward
swing in the hype cycle. The lack of clarity about why some data needs to be
on a decentralised network at all remains, as does the suspicion that other
ventures may just be offloading energy costs onto customers – no minor
concern as prices soar. Meanwhile some recent NFT releases have made
non-fungible tokens seem like a satire on the digital economy – a
Situationist joke. But one area where blockchain may have useful
applications is establishing a secure digital identity, according to a
techUK seminar this week. The Zoom event brought together four DLT
luminaries, from finance, government, agriculture, and digital identity
itself. The intention was to challenge misconceptions and set out a viable
route to market, according to Laura Foster, techUK’s Programme Manager for
Technology and Innovation. However, she then passed the chair to potentially
the most interesting speaker, Genevieve Leveille, key founder and CEO of
AgriLedger – a distributed-ledger app for the farming supply chain, who did
a good job.
Enterprise architecture in the agile era: Less policing, more coaching
One principle of agile EA is not to boil the ocean by collecting every bit
of information about an organisation before providing insights or
recommendations, says Gordon Barnett, principal analyst at Forrester. To
speed the process, agile EA practitioners refer to a “minimum viable
architecture” or “just enough architecture” to meet an urgent business
problem, making frequent changes to the EA process as needed. But, Barnett
warns, the key is to choose the right elements to include to ensure that
such a minimal architecture doesn’t limit its future usefulness. For
organisations that are heavily reliant on SaaS applications and the cloud,
“a minimum viable architecture helps hold together that distributed
ecosystem” with technology standards and more collaborative governance
models, even if it doesn’t provide a central repository of the distributed
assets that now support the business, Gartner’s Blosch adds. At SYNLABS
Jones began by concentrating on “the key pieces of information we needed to
understand the business in terms of the application portfolio” and narrowed
his search to, at most, “20 pieces of information about an application.”
Four Principles Every Organization Implementing Intelligent Automation Must Live By
Intelligent automation is a subset of artificial intelligence (AI). It is
the computerization of processes traditionally carried out by people. Moving
beyond current automation technologies (such as robotic process automation),
intelligent automation replicates more complex processes — especially those
that involve human decision-making. It gives organizations the opportunity
to increase efficiency, improve customer experience and generate new
revenues through automated digital products and services. But organizations
that take to the sky with intelligent automation programs — without properly
understanding the success factors — risk dropping quickly back down to
Earth. As François Candelon, Rodolphe Charme di Carlo, Midas De Bondt and
Theodoros Evgeniou wrote in Harvard Business Review, "For most of the past
decade, public concerns about digital technology have focused on the
potential abuse of personal data." But now, "attention is shifting to how
data is used by the software."
Architecting for Resilience Panel
When it's about starting up new to the technology, there's obviously a
strong pull towards the pre, and like, how do we connect with our supply
chain, and CI/CDs, and what gets deployed there? Where is the source of
truth of configurations of resiliency? Is it in my Git and my Git stuff? Is
it in a separate system? Where should I change what? How should it change? A
lot of the challenges are around setting up those organizational processes
in terms of who changes what, where, and how does that get approved?
Ultimately, then it gets to Nora's world, which is, if things do go wrong,
who's accountable? How do I recover? Who's alerted? How quickly? Simple
things to nail home at one point, which is, we do certain things like, ok,
every service, there should be a team that owns it. It should have an owner.
It's a very simple concept. You will be surprised how not implemented it is,
like our lack of implementation of that. I've heard stories of, this went
down, and we went down tracking, and we ended up at a service of like, who
wrote this? This dude left three years ago.
Network from home: how data privacy and security responsibilities must be shared
Having entire organisations working remotely is a relatively new phenomenon,
but traditional security advice remains very relevant. Remote workers should
consider the technologies available to support their remote security needs,
such as a password manager that allows you to use a variety of passwords and
rotate them often, without having to remember them all, but which makes it
difficult for hackers to access your different accounts based on a single
master password that could have been compromised when relied upon too often.
Equally, employees can upgrade their applications and tools to improve their
privacy posture. Search engines and browsers such as DuckDuckGo, Brave
Browser and Ecosia that give you more control over your privacy exposure can
help minimise the risk of attack and personal information loss. Network
firewalls are another tool to consider, which can help upgrade a home
network into an environment more consistent with that of the office by
monitoring network traffic, blocking malicious websites and allowing you to
moderate how others access resources.
The new rules of succession planning
The problem with identifying top candidates often lies in how a short list
is generated. Traditionally, the focus is on who the leader is without
significant weight put on what skills he or she needs to deliver on the
company’s strategy. If succession discussions are to be transformed into
more of an upstream process for the board—and members are to have a clear
understanding of what the company needs before discussing the best
candidates—then the process must account for three distinct and entirely
predictable challenges. Because they are predictable, these challenges can
be anticipated and overcome. First, start with the what and not the who.
Doing so will lay out a more realistic and substantive framework. Second,
from this vantage point, try to explicitly minimize the noise in the
boardroom. Ensure that the directors are using shared, contextual
definitions of core jargon, such as strategy, agility, transformation, and
execution. Third, root the follow-on analyses of the candidates in that
shared understanding, and base any assessments on a factual evaluation of
their track records and demonstrated potential in order to minimize the bias
of the decision-makers themselves.
Quote for the day:
"Leadership is the art of giving
people a platform for spreading ideas that work" --
Seth Godin
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