To turn reams of data into useful predictions, Cardea walks users through a pipeline, with choices and safeguards at each step. They are first greeted by a data assembler, which ingests the information they provide. Cardea is built to work with Fast Healthcare Interoperability Resources (FHIR), the current industry standard for electronic health care records. Hospitals vary in exactly how they use FHIR, so Cardea has been built to "adapt to different conditions and different datasets seamlessly," says Veeramachaneni. If there are discrepancies within the data, Cardea's data auditor points them out, so that they can be fixed or dismissed. Next, Cardea asks the user what they want to find out. Perhaps they would like to estimate how long a patient might stay in the hospital. Even seemingly small questions like this one are crucial when it comes to day-to-day hospital operations — especially now, as health care facilities manage their resources during the Covid-19 pandemic, says Alnegheimish. Users can choose between different models, and the software system then uses the dataset and models to learn patterns from previous patients, and to predict what could happen in this case, helping stakeholders plan ahead.
The initial shift toward digital financial services saw an ad hoc response from regulators. As new technologies come into play and tech giants like Google and Apple become increasingly disruptive in the financial industry, these transformations will force policymakers to identify emerging threat vectors and comprehensively address risk. In contrast to today’s mostly national systems of oversight, a global approach may be necessary to ensure stability in the sector, and we may see the rise of new licensing and supervisory bodies. The future of digital banking appears bright, but the unprecedented pace of innovation and shifts in consumer expectations demand a new level of agility and forward-thinking. Even as financial institutions attempt to differentiate themselves from competitors, co-innovation will become an integral part of success. People and technology will both play critical roles in these developments. Tech capabilities and digital services must be extremely resilient, constantly available at the time of customer need. Human capital, however, will be as crucial as any other asset. Leaders will have to know how to upskill, reskill and retain their talent to promote innovation.
We sometimes use artificial intelligence and machine intelligence interchangeably. This notion comes from our collaborations with author David Moschella. Interestingly, in his book “Seeing Digital,” Moschella says “there’s nothing artificial” about this: There’s nothing artificial about machine intelligence just like there’s nothing artificial about the strength of a tractor. It’s a nuance, but precise language can often bring clarity. We hear a lot about machine learning and deep learning and think of them as subsets of AI. Machine learning applies algorithms and code to data to get “smarter” – make better models, for example, that can lead to augmented intelligence and better decisions by humans, or machines. These models improve as they get more data and iterate over time. Deep learning is a more advanced type of machine learning that uses more complex math. The right side of the chart above shows the two broad elements of AI. The point we want to make here is that much of the activity in AI today is focused on building and training models. And this is mostly happening in the cloud. But we think AI inference will bring the most exciting innovations in the coming years.
Ecommerce is all grown up. It’s time to break away from the early-internet paradigm where online shopping was a new, “electronic” form of shopping. Today, almost all commerce involves varying degrees of digital elements (discovery, price comparison, personalization, selection, ordering, payment, delivery, etc.). The defining factor is not whether commerce is digital; rather, one defining factor is the optimal location for a retailer to meet a consumer’s needs. Shopping happens on a spectrum between home and the store. As such, ecommerce is better understood as commerce at home, and Amazon was the early winner. Great retailers focus on convenience or the experiential. In the new paradigm, certain retail truths persist. For example, all great retailers have focused primarily on either convenience retail or experiential retail. To be clear, any retail can be a great experience, but the priority matters. Amazon focuses ruthlessly on convenience. The outcome is a great customer experience. To drive growth, Amazon has prioritized speed and selection over consultation and curation. Amazon’s focus on convenience has yielded an (incredibly) high-volume, low-margin retail business.
AI may never reach the nightmare sci-fi scenarios of Skynet or the Terminator, but that doesn’t mean we can shy away from facing the real social risks today’s AI poses. By working with stakeholder groups, researchers and industry leaders can establish procedures for identifying and mitigating potential risks without overly hampering innovation. After all, AI itself is neither inherently good nor bad. There are many real potential benefits that it can unlock for society — we just need to be thoughtful and responsible in how we develop and deploy it. For example, we should strive for greater diversity within the data science and AI professions, including taking steps to consult with domain experts from relevant fields like social science and economics when developing certain technologies. The potential risks of AI extend beyond the purely technical; so too must the efforts to mitigate those risks. We must also collaborate to establish norms and shared practices around AI like GPT-3 and deepfake models, such as standardized impact assessments or external review periods.
An accelerated pace of digital transition, consumption of goods and services via app-based interface, and proliferation of data bring numerous risks such as biased decision-making processes being transferred to machines or algorithms at the development stage by humans, a Deloitte statement said on Friday. "These biases can be a threat to the reputation and trust towards stakeholders, as well as cause operational risks," it said. Partner, Deloitte India, Vishal Jain, said the pandemic compelled businesses and consumers to embrace digital technologies like artificial intelligence, big data, cloud, IoT and more in a big way. "However, the need of the hour is to relook at the business operations layered on digital touchpoints with the lens of ethics, given biases might arise in the due course, owing to a faster response time to an issue," he said. Societal pressure to do "the right thing" now needs a careful consideration of the trade-offs involved in the responsible usage of technology, Jain said, adding, its interplay becomes vital to managing data privacy rights while actively adopting customer analytics for personalised service.
All of our journeys are exquisitely different, yet come with a unique set of challenges that can blur our leadership lens if not properly focused. This can become a snowball of personal detriment. Therefore, your mental, physical, and emotional health is just as important (if not more) than your professional and economic health—they are interrelated. Identify a therapist, wellness clinician, spiritual leader, life coach, physical trainer and/or anyone who can support your becoming an even greater version of yourself. Let's call this person the "healer". Make time for physical activity, healthy food choices and spending time with loved ones. Ensure the same investment you make in your team members, you also make in yourself. It is up to you to create your rituals for personal success. What will they entail? ... Similarly to curating a list of your tribal elders, remember that you are also an elder to a younger leader in your collective. We all were afforded a different set of societal privileges based on constructs of race/ethnicity, gender, sexual orientation, cognitive and physical abilities, etc. I think it’s important to utilize some of these privileges to be an ally/co-conspirator to someone who may not have the same position in society.
The role of EA is closely connected to solutions architect, but tends to be broader in outlook. While EAs focus on the enterprise-level design of the entire IT environment, solution architects find spot solutions to specific business problems. EAs also work closely with business analysts, who analyse organisational processes, think about how technology might help, and then make sure tech requirements are implemented successfully. Looking upwards, EAs tend to work very closely with chief information officers (CIOs). While the CIO focuses on understanding the wider business strategy, the EA works to ensure that the technology that the organisation buys will help it to meet its business goals, whether that's improvements in productivity, gains in operational efficiency or developing fresh customer experiences, while also working with others – like the security team – to ensure everything remains secure. Nationwide CIO Gary Delooze is a former EA who says a really good enterprise architect will bring the business and IT teams together to create a technology roadmap.
To appreciate the ways in which blockchains can support complex collaborations, consider the task of shipping perishable goods across borders — a feat that requires effective coordination among suppliers, buyers, carriers, customs, and inspectors, among others. When the parties pass the cargo to another, a flood of information is transferred with it. Each party keeps their own record and tends to communicate with one partner at a time, which often leads to inconsistent knowledge across participants, shipping delays, and even counterfeit documentations or products. If, say, the buyer expects the goods to be constantly cooled throughout the shipping process and temperatures exceed agreed thresholds, a dispute is likely to occur among the buyer, the supplier, and the carrier, which can devolve into lengthy wrangling. The carrier may haggle over the liability to lower the compensation, arguing that customs delaying the transportation or the inspectors who improperly operated with the cargo are the ones to blame. The buyer will ask the supplier for remedy, who in turn needs to negotiate with the carrier. And so on. Problems like these can manifest in any collaboration that requires cumbersome information sharing among partners and may involve disputes in the process.
Individuals are starting to pay attention to organizational vulnerabilities that compound risks associated with managing, protecting, and enabling access to information, ranging from poor data quality, insufficient methods of protecting against data breaches, inability to auditably demonstrate compliance with numerous laws and regulations, in addition to customer concerns about ethical and responsible corporate use of personal data. And as organizations expand their data management footprints across an increasingly complex hybrid multicloud environments, there has never been a greater need for systemic information risk management. ... In general, “risk” affects the way that a business operates in a number of ways. At the most fundamental level, it inhibits quality excellence. However, exposure to risks not only has an effect on project objectives, but it also poses threats of quantifiable damage, injury, loss, liability, or other negative occurrence that may be avoided through preemptive action. Using the Wikipedia definition as a start, we can define information risk as “the potential for loss of value due to issues associated with managing information.”
Quote for the day:
"The actions of a responsible executive are contagious." -- Joe D. Batton