Artificial Intelligence (AI) is set to have a multi-pronged impact this year. First of all, AI will have a major impact at the workplace. This will in the long run affect employment, with retooling of job profiles and a reassessment of the desired skills. However, at present it will affect companies’ talent recruitment more as they will need to do a complete data backed analysis on what different functions to address this year. The interesting this is that this recruitment will not be driven by the technologists alone, but by specific domain experts. There has long been a debate on the return-on-investment (ROI) in the use of Big Data. This is set to be resolved with the use of AI. While cyberattacks have unfortunately already become more common, their severity is set to further rise, ringing in the alarm bells. AI will need to be transparent, provable and explainable for it to be relevant to all kinds of stakeholders. While USA remains the dominant power in such tech, China may soon take over. The likes of Canada, Japan, Germany, the UK and the UAE are also there in the pipeline. The onus on responsible use of AI won’t lie on the prerogative of tech companies singlehandedly, but will be a shared need.

Source:https://www.strategy-business.com/slideshow/Artificial-Intelligence-What-to-Expect-in-2018?gko=5d351

Uploaded Date:27 February 2018

The bitcoin cryptocurrency has been a lot in the news due to its exponential rise in value in 2017, before sliding down again recently. However, the bigger picture is that of the Blockchain technology which powers Bitcoin and all such cryptocurrencies. In a study anchored by MIT Sloan lecturer Michael Casey, it is explained how blockchain is becoming something of a “truth machine”. It is leading to a consensus of facts now, which in fact is the very essence behind human civilizations. Enormous funds are spent on tallying ledger books and balance sheets, because of the breakdown in trust. That is why blockchain technology needs a decentralization. It is already being utilized in various real-life scenarios such as an algorithm powered by blockchain driving a part of the World Food Programme’s operations in the Syrian refugee camps in Jordan. This business innovation in such a critical environment can solve problems for thousands of people, often at the mercy of clerical inefficiencies. Blockchain could also evolve into a Tragedy of Commons sort of problem.

Source:http://mitsloan.mit.edu/newsroom/articles/blockchains-applications-reach-further-than-you-think/?utm_source=mitsloantwitter&utm_medium=social&utm_campaign=truthmachine

Uploaded Date:27 February 2018

While AI (Artificial Intelligence) seems to be everywhere, amidst the hoopla over stars such as Alexa, Alpha Go or Siri, the technology still has a lot to improvise. While innovators say that AI will soon be a part of almost everything, it is better to keep a cautious eye out. As per a recent report by the McKinsey Global Institute, even within sectors, there remains a massive disparity between the leaders and followers. The sectors on top of the AI adoption rates are financial services, high tech, communications, logistics, healthcare and tourism. This is followed by a middle pack comprising media, professional services, retail, energy, education, automotive and consumer packaged goods. Building materials and construction industry is falling behind. Five major limitations have been identified by this study. The first of them is, data labelling, which is the process of each data set being categorized by humans. This leads to a reinforced learning using trial and error. Another limitation is the requirement of vast data warehousing to get any operation underway. A third is that while AI provides quantitative analysis, it does not explain the bigger picture. AI also does not have the ability to improvise in learning, as rather it is too generalized. Ideally, AI is supposed to be free of biases, but ultimately all algorithms are created by humans, so inherent biases creep in. A calibrated approach with lateral thinking is needed to solve this, with a sophisticated strategy for business analytics.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/what-ai-can-and-cant-do-yet-for-your-business?cid=other-soc-twi-mip-mck-oth-1801&kui=1UXNVzIzR8YwtGkEDN4iUQ

Uploaded Date:13 February 2018

The reputation economy is one where ratings given to service providers are broken down to produce a value on each person or organization. This is true for drivers of Uber or hosts in Airbnb. This social graph determines the worth of every person. In fact, a study says that in the US alone seventy percent of companies scan candidates’ social media ratings during talent recruitment rounds. Such methodology however is flawed. As an example, one can cite the fact that nearly four-fifths of Americans use Facebook, but far lower numbers similarly use Twitter or Instagram. This prevents genuine triangulation across the three fronts. There is a lot of frivolous data available which can lead to unintended results if weighed too much importance. Similarly, a lot of algorithms go wrong such as COMPAS used by the US justice system which has been proven to be racially biased. An unintended consequence of the reputation economy is that everyone is being judged all the time. A lot of service providers have adopted the stance of “social cooling” where they are expected to remain silent. With data protection now such a major point of discussion globally, this reputation economy will similarly need to be scrutinized for its effect on people.

Source:https://hbr.org/2018/01/as-ai-meets-the-reputation-economy-were-all-being-silently-judged?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18921171&spUserID=OTY0OTMwNTk5NwS2&spJobID=1182008306&spReportId=MTE4MjAwODMwNgS2

Uploaded Date:13 February 2018

There is a lot of debate at present about the future of Artificial Intelligence (AI) and how that will change work. Broadly, the views may be separated out into five schools of thought. The first are the Utopians who are very optimistic as they feel robots will take more work leading to high economic growth. The Dystopians feel the other way-round, as they feel that machines will win a Darwinian struggle till the end, displacing humans. Mass unemployment, and real wage decline will most heavily be felt in Europe and North America. The Technology Optimists on the other hand feel that business innovations will improve quality of life but only when companies fully leverage those. The Productivity Skeptics feel that while robots do have the potential to enhance productivity, due to several other societal challenges, the net effect will be negligible. The Optimistic Realists are those who feel that digitization and AI in particularly can lead to rapid advancement in several sectors where research will be turned on. In order to ensure a bright future in human-machine interaction, technology needs to be used so that operating models may be redesigned and human skills can get augmented by machine usage. A complete redesign of jobs needs to be done. Employees’ innate abilities need to be leveraged so that an intelligent enterprise may be forged.

Source:https://hbr.org/2018/01/how-will-ai-change-work-here-are-5-schools-of-thought?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18894202&spUserID=OTY0OTMwNTk5NwS2&spJobID=1181669277&spReportId=MTE4MTY2OTI3NwS2

Uploaded Date:06 February 2018

It is tempting to blame Artificial Intelligence (AI) for a lot of impending doom. Apparently, a lot of jobs, especially the routine ones will be taken over by bots and robots. In this scenario, the art and science of leadership will also be under the scanner. A lot of traditional leadership roles could now be performed by AI powered tools. This especially relates to the ‘hard’ parts of leadership such as dissemination of information. Those aspects requiring soft skills such as objective decision making and team mentorship will also be affected but in different ways. One way in which this change will take place is the level of humility that will now be expected from leaders. They can no longer expect an easy ride, as due to constant tech changes, they will need to periodically upgrade their learning. Companies such as Nestle have designed their corporate training programmes to include a dose of reverse mentoring where youngsters will train their senior leaders on newer work patterns. Leaders will also now need to be more adaptable as these changes will need to be incorporated constantly to ensure the right digital transformation. They will need to engage more with their team members. A vision needs to be articulated by these leaders to ensure gains in spite of near-term uncertainty as done at Amazon, Tencent Google, Alibaba, Facebook and Tesla.

Source:https://hbr.org/2018/01/as-ai-makes-more-decisions-the-nature-of-leadership-will-change?utm_medium=email&utm_source=newsletter_daily&utm_campaign=dailyalert&referral=00563&spMailingID=18878522&spUserID=OTY0OTMwNTk5NwS2&spJobID=1181524093&spReportId=MTE4MTUyNDA5MwS2

Uploaded Date : 06 February 2018

The usual narrative goes that robots, algorithms, software and artificial intelligence do not suffer from human flaws. Apparently, they behave uniformly with all, follow orders and do not get sick or tired. Yet this perception is flawed, as all these algorithms and software are ultimately created by humans, and their flaws inherently get embedded in. Embarrassing and outright disgusting cases abound with the worst being Microsoft’s chatbot having to be taken off as it had learnt to spout racist language. So, while these tools have tremendous business analytics capabilities, they lack empathy, judgement and the sense of self-awareness. One of the reasons for this is that the engineers who design these tools or virtual characters, may be experts at STEM, but lack the wider understanding of emotion on society, economy and human interaction. A lot of such code is created in intellectual isolation. This is why it is pertinent that coders and engineers get some lowdown on works of liberal arts so the products curated may be more humanized.

Source:https://www.strategy-business.com/blog/Why-Artificial-Intelligence-Needs-Some-Emotional-Intelligence?gko=520ac

Uploaded Date:19 January 2018

Artificial Intelligence (AI) has increasingly been spoken about the last few years as the next major frontier. The good part is that now the early adopters of AI have started experiencing some gains. Digital native tech companies such as Amazon, Google and Baidu have already invested a lot of money in to their internal researches. In addition, AI is making work easier for retailers, public utilities and carmakers. The use of AI among non-tech companies is still relatively low and can be improved. The one biggest impact so far has been the enormous data warehousing capabilities now at play. Enormous gigabytes of data are being created worldwide. Telecom and financial services are two of the other top AI using industries as per a study by McKinsey. The USA is on top of the pile among countries absorbing AI investment with about two-thirds of the total. This is followed by China, with South Kore and the UK coming next.

Source:https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies?cid=other-eml-ttn-mgi-mgi-oth-1712

Uploaded Date:19 January 2018

As the example of the MD Anderson Cancer Center would testify, ambitious world-changing projects have long been thought of being done with the help of Artificial Intelligence (AI) based technologies, but it is the mundane, daily aspects where AI’s use has been more effective. There are three major ways in which AI supports business needs. One is in process automation such as data warehousing from email and call center records, communication and further replacement of lost information or physical products, processing legal information and extracting information from across disparate document types. Another is providing business intelligence after sieving through enormous chunks of data. The third is active engagement with the customer base, employees and other key stakeholders. A four-step process has been adopted successfully by companies that have integrated AI into regular business processes. Firstly, the technology needs to be understood thoroughly. Then a portfolio of projects needs to be recognized. At this stage, the opportunities and bottlenecks need also to be acknowledged and technology selected. After this pilot projects need to be launched on test basis. After all this is done, the operations need to be scaled up to provide business feasibility.

Source:https://hbr.org/2018/01/artificial-intelligence-for-the-real-world?utm_campaign=hbr&utm_source=twitter&utm_medium=social

Uploaded Date:19 January 2018 

Autonomous or self-driving cars are set to revolutionize major aspects of life in the coming years. Start-ups and auto giants likewise are exploring ways to develop these on a far lager scale. It will even disrupt the present pattern of town-planning with special emphasis on lanes for self-driving cars. Consulting and professional services giant PwC recently won the Alconics award for its application at the recent AI Summit San Francisco. It beat off in the competition several Ai-based outfits such as Daisy, Luminoso, Ui Path and Digital Genius. PwC’s Director of its Business Analytics division claims that AI will not prove to be successful unless integrated with the field level business use. PwC’s success in develop this app was down to its futuristic approach towards city maps, electric charging points, existing customer pick-up locations and their wait times. Thus, its technical prowess combined with its domain expertise. The concept of ‘data fly-wheel’ has been proposed. According to this, a positive feedback loop needs to be developed so that data warehousing can be performed. This will provide essential insights on customers’ requirements, so talent may be aligned likewise.

Source:https://aibusiness.com/pwc-data-strategy-architecture-ai/

Uploaded Date:13 December 2017

Artificial Intelligence (AI) as a field shows no signs of abating. In a latest development, Swiss financial services giant UBS Group AG in collaboration with Amazon is set to use the latter’s Alexa solutions in the field of wealth management. The financial services industry as it is has moved on from its earlier avatar as an active management tool to passive management, will now take a further step into the background with smart machines doing a lot of the work, just as in Blackrock. Further, business consulting which is a US$ sixty billion worth industry is set to face massive repercussions. More complex decisions such as capital allocation, budgeting, marketing, human resources and even the highly human intensive corporate strategy will increasingly be performed by AI much to the chagrin of McKinsey, BCG, Bain and others. Huge amounts of data can be processed by smart computers much quicker than humans can ever do. In addition, in spite of the best of efforts, some biases inadvertently creep into human decisions, something that is not possible with robots. That is why Alexa, Google Home or Siri can only rise in stature to continue on from their present status as Quant Consultants or Robo-Advisers.Source:https://hbr.org/2017/07/ai-may-soon-replace-even-the-most-elite-consultants?utm_campaign=hbr&utm_source=twitter&utm_medium=social

Uploaded Date:21 October 2017