Exciting, risky and widely misunderstood, cryptocurrency has been the investment story of the last decade. But, with their fortunes falling in 2022, are Bitcoin and all of the digital tokens that came after still investments worth making?
According to a new GOBankingRates survey of more than 1,000 American adults, fewer than one in four people invest in cryptocurrency — and experts and industry watchers are seeing a lot of them making many of the same mistakes.
Here’s a look at some of the most common crypto-investing errors — and what you can do to avoid them.
Overestimating Its Complexity
Most of the 76.66% of people who don’t invest in crypto avoid the investment because they don’t understand it. It is, after all, highly complex — but the same could be said for the stock market.
“Blockchain and distributed ledger technology can be difficult to understand, but so are most traditional financial products,” said Harry Clynch, a writer for Disruption Banking, a crypto-focused online financial publication. “Trading Bitcoin is no more difficult than trading on foreign exchange markets, for example.”
Yes, crypto tech is complicated and unfamiliar — but so are the algorithms behind Facebook and Amazon, and you don’t need an advanced degree in computer science to subscribe to Prime or scroll your newsfeed.
“The internet as a technology is complex. However, no one needs to understand that complexity; they just need to be able to use it,” said Edson Ayllon, product manager for dHEDGE, a platform offering social asset management on the blockchain. “Crypto is the same in this way.”
Continue reading: https://www.gobankingrates.com/investing/crypto/mistakes-new-crypto-investors-are-making-how-to-avoid-them/

There are many different types of cryptocurrencies. In this article, we will discuss the most popular types. Each type has its own unique features and benefits. How do you know which type is right for you? This guide will give you some tips on how to choose the right type of cryptocurrency, along with how to accept this digital currency as payment.
How Many Different Cryptocurrency Types are there?
The number of different types of individual cryptocurrencies varies, and they all have price fluctuations. In 2018, there were 1,583 different individual types, according to the price-tracking website for crypto assets coinmarketcap.com.
While you probably heard and saw the most about Dogecoin for a time, courtesy of gregarious Tesla CEO Elon Musk, the most popular form of this digital money are Bitcoin and Ethereum. You’ll usually see these two forms of digital money reign at the top of the cryptocurrency market list in terms of highest market capitalization.
How to Choose the Right Type of Digital Assets and Cryptocurrency
Acquiring digital assets and cryptocurrency is one of the most important investment decisions that you will ever make. With so many different types of digital currencies available, it can be overwhelming to choose the right one. Additionally, when it comes to choosing the right type of cryptocurrency, there are many factors you need to consider.
First and foremost, do your research. This is probably the most important advice. Do not take anyone’s word for it when it comes to assets and cryptocurrencies. Many frauds and scams abound, so research everything thoroughly before you make any decisions.
Here are a few other factors that you should consider when choosing the right type of cryptocurrency for your needs:
Continue reading: https://smallbiztrends.com/2022/06/types-of-cryptocurrency.html

Web3 (also known as Web3.0 and sometimes stylized as web3), In everyday conversations, Web3 is an umbrella term for the blockchain, cryptocurrency, and NFTs.
Web 3.0 refers to the next phase of the evolution of the web. Web 3.0 is built upon the core concepts of decentralization and greater user utility. (1)
 To understand Web3 deeply, we first need to understand Web1 and Web2.
Evolution of the Web
Web1 ( 1989-2005)
Web1 refers to tools for publishing static information owned and considered proprietary, fact-checked, and attributed.
Web2(2005-Present)
Web 2.0 applications are web pages that visitors can add to or change. Users add information, as with the product reviews on Amazon.com, informing other users in reader-friendly ways.
Web3 (yet to come)     
It refers to the next generation of internet evolution that would make the web more intelligent. It enables the evolution of web utilization.
WEB2 vs. WEB3 
Web2 represents the version of the internet most of us know today. An internet dominated by companies that provide services in exchange for your data.
Web3 refers to decentralized apps that run on the blockchain.Web3 will go beyond Web2 offerings such as streaming video, online shopping, and social media.                         
What is the point of Web3?
Web3 is being approved as the future of the internet. Web3 is defined as “the internet owned by the builders and users, adapted with tokens.” (2)
The more complicated but specific way to think about Web3 is the internet owned by users.
That’s the dream of crypto boosters, who say the integration of blockchain technology will lead to an egalitarian internet.
Web3 is the upcoming internet generation where apps and websites will process information in an intelligent human-like manner using Big Data, Machine Learning, Artificial intelligence, and more.  
 Continue reading: https://coinnounce.com/what-is-web3-and-what-future-does-it-hold/

Looking at our world today, there is no shortage of ideas, with new ideas coming up every day, nay, every hour. But, ideas are much more powerful than they seem on the surface. Consider that with some funding and the help of a strategic team, an idea can become something real ––  a new technology or a solution to a major world problem. With so much value on the line, it is no secret that it becomes a human tendency to want recognition for ideas. 
Unfortunately, it is not often the original idea creator that gets the credit and history has given many examples of that. For instance, although Alexander Graham Bell did bring the telephone to life, it was Antonio Meucci who created the first voice-communication device in 1871. The difference between the two is Antonio, unlike Alexander, didn't pay the entirety of the amount needed to register the patent for his idea.
Perhaps, the worst part of it is that the invention of the telephone was not an isolated event. In a more recent example, Meta (former Facebook), a platform that has arisen as the largest social network on the planet today, became part of a major lawsuit when the Winklevoss twins filed a lawsuit against Mark Zuckerberg for a stolen idea. Allegedly, the twins partnered with Mark Zuckerberg to help bring their vision to life, an event that later inspired him to develop his own social networking site secretly.
Continue reading: https://cointelegraph.com/news/blockchain-redefines-the-framework-for-ip-with-architecture-fit-for-web3

For many women, a career as a software engineer can seem daunting. This is an area where women are traditionally underrepresented so many women dismiss it because of the perceived barriers to entry and the under-representation of females in the space. But, because there’s a strong need for software engineers because of Australia’s tech skills shortage, this is an appropriate time for women to look a bit more closely at just what a career in software engineering will give them – and what’s required of them to work in this field.
The Holberton School Australia is a new school which is making women – and men – who wouldn’t normally consider a job in IT, consider these types of roles. Holberton School is a dedicated computer science school originally founded in Silicon Valley in 2016 to bridge the gap in the education system for software engineers. With branches in quite a few countries now, the Australian branch started operating early this year, offering the software engineering foundations course.
What’s different about the Holberton School? Well, it takes a new approach to software engineering and in fact, the school makes it possible to become a fully-fledged software engineer in around nine months. There’s a lot of hands-on training and working in groups with other students, and the end result is the students are capable of working as software engineers. All up it’s an attractive proposition for many young people because it’s an interesting job and one of the advantages is software engineers are well paid.
Continue reading: https://womenlovetech.com/why-a-career-in-software-engineering-ticks-all-the-boxes/

Bengaluru: Even as the war for talent continues and roles in technology and product command a premium, a host of new-age companies are prioritizing moving the needle on their diversity numbers. According to Nasscom data, women constitute 35% of India's technology industry, a figure that companies like Wakefit, Urban Company, Mpower Financing, EnKash and Simplilearn are looking to increase through a host of initiatives.
The focus is not just on attracting more women to product and technology roles, but also driving a more inclusive culture that ensures female talent is retained.
Last month, Urban Company set up a taskforce to push for representation, community building and sensitization of hiring managers, as well as regularly liaising with company leadership on proactive steps that could be taken to build better female representation.
“Our business represents a diverse marketplace and hence we are able to attract diverse talent. Our focus is more on the retention part - through driving success stories of women leaders in tech and product roles, giving access to role models, and building structured career development plans for female talent,” Neha Mathur, senior VP of people success, Urban Company, told ET.
Continue reading: https://economictimes.indiatimes.com/tech/startups/startups-accelerate-hiring-of-women-in-product-technology-roles/articleshow/92237623.cms

Any business with a credit and collections function will recognize the “promise to pay” phenomenon. It’s the tendency of customers, when chased by a collections agent, to exaggerate how much they will pay of a debt and how quickly. But while it is a natural human instinct, when confronted by someone making demands of you, to tell them what they want to hear, this makes it difficult for businesses to manage their debts; they don’t really know who will pay what and when.
Irish start-up business Webio, which is today announcing a $4 million Series A fund-raising round, thinks the possibility of confronting the promise to pay problem could be just one benefit of its communications technology. “People feel much more able to be honest when they’re communicating in text form, rather than having a voice interaction,” explains co-founder and CEO Cormac O’Neill.
Launched in 2016, Webio has built a workflow and communications platform aimed at businesses such as utility companies, financial services firms and e-commerce merchants, all of which have to put significant resources into debt collection. The front end of the platform is a machine-learning driven chatbot through which these businesses can automate their conversation with customers via channels such as text messaging, WhatsApp and web chat.
Simple queries – such as when payments are due and how to make them – can be solved without human involvement. More complex issues are automatically routed to the company’s agents, with Webio’s technology able to identify such cases through analysis of the chatbot conversation.
“Conversations about debt are very stressful for both the borrower and the agent,” says O’Neill. “Having those conversations through a textual interface can reduce that stress – then you refer customers with particular problems or vulnerabilities to someone who has the expertise to help.”
Continue reading: https://www.forbes.com/sites/davidprosser/2022/06/16/why-ai-could-be-the-answer-as-companies-chase-down-debt/?sh=4a060943a338

Since the pursuit of machine learning began in the mid-20th century, the technology industry has focused on building artificial intelligence (AI) capabilities that replicate human intelligence. It’s only in the last five to 10 years, as AI has become more of a practical reality, that discussions around ethical AI have reached the mainstream. And although there’s general agreement on the principles of ethical AI (e.g., transparency, justice and fairness, non-maleficence, responsibility and privacy), there’s little agreement on how to apply and operationalize them in an organization.
Consider findings from a recent survey by IBM, which show that despite a "strong imperative" for the need to advance ethical AI, there's still a gap between business leaders’ intentions and meaningful action. Nearly 80% of CEOs stand ready to embed AI ethics into their companies' business practices, but less than a quarter have operationalized them. And less than 20% of those surveyed said their company’s actions were consistent with its AI ethics principles.
Sadly, these findings are neither shocking nor uncommon.
The Barriers To Successful Implementation Of Ethical AI
Researchers from Microsoft Research and Carnegie Mellon University worked with nearly 50 machine learning practitioners from more than a dozen tech companies to compile an ethical AI checklist. In the course of their work, staff members heard a common refrain: Speaking up about ethics issues exacted a social cost and could adversely impact a person’s career because advocating for AI fairness could slow the pace of work and lead to missed deadlines.
When ethical issues do arise, all too often the knee-jerk response for most companies has been to implement better algorithms or tech-based controls that help rein in bias or other unethical practices. But most of these same practitioners told the researchers that any solution to ethical AI issues should be both technical and non-technical in nature. Why? Reasons included:
Continue reading: 
https://www.forbes.com/sites/forbestechcouncil/2022/06/16/operationalizing-ethical-ai-from-the-c-suite-to-the-data-pipeline/?sh=3aa0253aa198

Artificial intelligence is billed as the future of everything—a magical panacea to all of the world’s challenges, heralding a utopian future where algorithms will know exactly what’s required and when. Is the future of audit really all about AI, or is it just hype?
Challenges Facing Audit
It’s important to start with a high-level overview of the challenges audit faces today. Solving the challenges of trust, talent and technology is going to be the key to getting a glimpse of what audit will look like tomorrow and beyond.
1. Trust
There is a general sentiment that auditors have lost the trust of the people who rely on them for accurate financial information. This isn’t pervasive or threatening, but for a profession that prides itself on its reputation, each new accounting scandal jeopardizes this hard-won stature.
2. Talent
The “Great Resignation” is well documented, as are statistics showing that numbers entering this industry are down across the board. Another key element here is that for audit—like many other professions—tomorrow’s auditors are looking to be proficient in coding and the latest algorithmic developments in order to remain relevant and be positioned to add value.
3. Technology
From a technological perspective, there are necessary advancements being implemented so auditors can provide the assurance that users rely on. Financial transactions are getting more complex, new technologies such as the blockchain are increasingly relevant and cryptocurrencies are becoming mainstream. If an auditor doesn’t have a deep understanding of these areas touching almost every business today, how can they render an opinion?
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/15/is-ai-the-future-of-audit-or-all-hype/?sh=1d3fe3e12d6d

It's Monday morning and you've just begun your work week. You have your coffee and sit at your computer ready to take on the day— and then it hits you — you have two blog deadlines to be submitted by the end of the day. Right before the panic hits its peak, you remember you have an AI-powered copywriting assistant. If this sounds like you, it's time to leap into 2022 and explore the remarkable world of AI copywriters. If you're not already using one, here are eight reasons why you should start right now.
What's an AI-powered copywriter? AI copywriting is the process of content generation through machine-learning software. This is done by training an algorithm to search through millions of web pages for patterns, and then using that knowledge to craft new content on a set topic. Using the latest in natural language processing, artificial intelligence is now able to mimic and understand complex human emotions.
1. Save time
Copywriter tools can give you a ton of material to work with in seconds allowing you to skip over your tedious research and outline development. You can take the best parts of what the AI writes and combine it with your own creativity to piece together your content in half of the time. Manage your time better while not budging on quality.
2. Improve ROI
A well-executed blog strategy and call to action can drive high volumes of targeted traffic to your website. Strategic on-page content will keep people engaged with your site and encourage them to sign up for your email list. Educational email content will keep them interacting with your brand until they are ready to purchase. What do all of these things have in common? Top notch copy. Oh — and a lot of time and effort when performed manually.
While a solid content strategy can yield remarkable results, it is a laborious task that can be resource intensive. Implementing AI as a tool in your copywriting process can streamline your content strategy and optimize efficiency improving your overall ROI.
Continue reading: https://www.entrepreneur.com/article/426695

The most diverse tech pipeline in the world won’t ultimately make a difference if the women who make it into tech are held back by organizational cultures that, consciously or not, incentivize their silence. While it may be true that women have the tendency to want and expect their work to speak for itself, the truth is that being vocal at work has always been a minefield for women. And data from the last two years shows that the move to online and “hybrid” work has only made things worse. As we contemplate a permanent shift to the hybrid workplace, it’s more urgent than ever that leaders commit to removing the barriers that get in the way of women sharing their voices and ideas.
Here are five simple things every executive can do to support the women on their teams finding their own voice:
Choose female spokespeople. When teams give you a readout, make sure that the spokesperson for the team rotates so that the women on the team are given as much opportunity to present as their male counterparts.
Barrier you’re breaking down: Research by Victoria Brescoll at Yale shows that “when male executives spoke more often, they were perceived to be more competent, but when female executives spoke more often, they were given lower competence ratings.” And these were executives! No wonder so many women are extremely reluctant to self-promote. Plus, women’s ideas are often attributed to men. For these reasons and a slew of others, your female employees may be understandably hesitant to volunteer as the spokesperson for a team project. To make matters worse, women often conflate being deferential with being a good “team player,” and may therefore lose out on critical opportunities for exposure to senior leadership, which can ultimately affect their chances for advancement.
Continue reading: https://www.forbes.com/sites/judithspitz/2022/06/14/five-ways-tech-leaders-can-support-women-on-their-teams-finding-their-own-voice/?ss=cio-network&sh=6635a23b3a84

By now, we’ve all heard some version of the story. On December 2, after a protracted disagreement over the release of a research paper, Google forced out its ethical AI co-lead, Timnit Gebru. The paper was on the risks of large language models, AI models trained on staggering amounts of text data, which are a line of research core to Google’s business. Gebru, a leading voice in AI ethics, was one of the only Black women at Google Research.
The move has since sparked a debate about growing corporate influence over AI, the long-standing lack of diversity in tech, and what it means to do meaningful AI ethics research. As of December 15, over 2,600 Google employees and 4,300 others in academia, industry, and civil society had signed a petition denouncing the dismissal of Gebru, calling it “unprecedented research censorship” and “an act of retaliation.”
The company's star ethics researcher highlighted the risks of large language models, which are key to Google's business.
Gebru is known for foundational work in revealing AI discrimination, developing methods for documenting and auditing AI models, and advocating for greater diversity in research. In 2016, she cofounded the nonprofit Black in AI, which has become a central resource for civil rights activists, labor organizers, and leading AI ethics researchers, cultivating and highlighting Black AI research talent.
Losing her job didn’t slow Gebru down. The following week, she took part in several workshops at NeurIPS, the largest annual AI research conference, which over 20,000 people attended this year. It was “therapeutic,” she says, to see how the community she’d helped build showed up and supported one another. Now, another week later, she’s just winding down and catching her breath—and trying to make sense of it all.
On Monday, December 14, I caught up with Gebru via Zoom. She recounted what happened during her time at Google, reflected on what it meant for the field and AI ethics research, and gave parting words of advice to those who want to keep holding tech companies accountable. You can also listen to a special episode of our podcast, In Machines We Trust, for highlights from the interview. (Google declined a request for comment on the contents of this interview.)
Continue reading: https://www.technologyreview.com/2020/12/16/1014634/google-ai-ethics-lead-timnit-gebru-tells-story/

Have you ever wondered what's needed to get a job as a small Unmanned Aircraft System (sUAS) commercial drone pilot? I'll explain below, along with the required skills and experience someone would need to successfully secure a drone pilot job.
Pilot Certification
A person must successfully pass the test for the Federal Aviation Administration (FAA) Part 107 Remote Pilot Certification. It’s required for any applications of drones that have either direct or indirect monetary compensation.
There are courses available to prepare you for this exam because it includes very specific aviation knowledge. Topics covered include regulations relating to small Unmanned Aircraft Systems; airspace classification, interpretation of sectional navigation charts, operating requirements and flight restrictions; aviation weather sources and effects; small unmanned aircraft loading and performance; emergency procedures; aeronautical decision-making and crew resource management; radio communication procedures; physiological effects of drugs and alcohol; airport operations; and maintenance and preflight inspection procedures.
Before testing, students need to study and memorize information to pass the “Unmanned Aircraft – General” test. This test includes 60 questions dynamically spooled individually from a knowledge base of 300 questions for each person testing. It requires a passing score of 70%. The test costs $175, paid separately to the Knowledge Testing Center. Additionally, there is a required recurrent Part 107 test every two years done online to remain compliant.
You can get an FAA Remote Pilot Certification without ever having flown a drone! The FAA doesn’t require any practical or hands-on flight skills test for certification. It seems to me this is like giving out automobile driver’s license without ever driving a car. And just the certificate alone certainly will not get you a job.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/15/how-to-become-a-small-unmanned-aircraft-system-drone-pilot/?sh=63a051ab313a

We speak with Merav Ozair, Blockchain Expert & FinTech Professor at Rutgers Business School about the differences between Web3 and the metaverse, and how soon they will be integrated into our daily lives, along with the biggest challenges standing in the way of adoption.    Could you give us a quick rundown of what Web3 and the metaverse are, and what their similarities and differences are?  People use the terms metaverse and Web3 interchangeably, as if they mean the same thing. They are not the same, although they do relate and can complement each other. Broadly speaking, Web3 is the evolution of Web2, the internet that exists today, from a centralized internet owned and controlled by centralized companies, to a decentralized peer-to-peer internet, where no one entity can claim control. Web3 is a concept for the next generation of the internet. It is the evolution of how users are able to control and own their creations and online content, digital assets and online identities. Unlike Web2, where centralized companies, which provide the service, control and own all of our data, Web3 users can create content while owning, controlling and monetizing them through the implementation of blockchain technology. The metaverse is how virtual spaces will merge and integrate into our lives that we will be able to interact with seamlessly. It's not yet a concrete reality. The vision of it is a 3D immersive world where we will spend time socializing, working, entertaining, learning and more. It is the combination of virtual reality (VR), augmented reality (AR), mixed reality (MR), gaming, cryptocurrencies, social media and much more. In other words, the metaverse is a new way for people to use the internet by transforming it from 2D to 3D. Instead of browsing and interacting with web content on 2D screens on computers or phones, these would be transformed into three-dimensional objects, where users could walk around inside the webpage and interact with other users’ avatars. The metaverse can be either centralized, owned by a centralized company like Meta, or decentralized. If users’ ownership is prioritized, then it is important that the implementation of the metaverse be a decentralized one. This can be achieved by the set of rules and guidelines Web3 provides, which is how the two different concepts can come together.
Continue reading: https://www.nasdaq.com/articles/challenges-facing-the-adoption-of-web3-and-the-metaverse

Bitcoin (BTC) is a decentralized peer-to-peer network made of computers, or nodes, that run the Bitcoin software and accept a set of proof-of-work (PoW) consensus rules to validate and broadcast transactions on the blockchain. This process occurs without the intermediation of a third party, making blockchains trustless mechanisms.
In traditional payment methods, transactions are validated by centralized parties like banks and payment processors who check that the spender has enough money available to perform that purchase. 
In the Bitcoin blockchain, traditional third-party payment systems are replaced by a distributed network of node operators and miners who validate transactions without censorship or permission. 
Learning what nodes do and how they work helps understand what occurs behind the settlement of a transaction. Anyone can become a Bitcoin node operator and participate in securing the network by simply downloading the Bitcoin Core software, thus making the blockchain transparent, immutable and decentralized. 
What is a Bitcoin node?
Nodes are pillars of the Bitcoin network. These nodes continuously monitor the blockchain and its complete transaction history to prevent access to non-legitimate transactions that attempt to spend their Bitcoin twice fraudulently, also known as the double-spending issue.
Any computer downloading the Bitcoin software that will join the Bitcoin network is called a node. The most popular client and software implementation of full nodes is Bitcoin Core; its latest release can be found on the GitHub page.
A node holds the complete history and chronology of the Bitcoin blockchain, which is like a ledger, and contributes to the security of the Bitcoin network through the consensus mechanism because nodes will reject any transaction that breaks consensus rules.
How many Bitcoin nodes are there? It is difficult to assess the exact number of active Bitcoin nodes, as users can choose to connect privately in order not to reveal or count them. 
There are very contradicting figures between one source and another. Some sources only calculate that there are just over 13,000 Bitcoin nodes. On the other hand, popular Bitcoin Core developer Luke Dash Jr estimated about 83,000 Bitcoin Core nodes were active in Jan. 2021 while recording a steep decline in 2022 to roughly 50,000. 
The data is even more alarming, considering over 200,000 Bitcoin nodes were running at the peak of the 2017 bull market. The more active and connected nodes to the Bitcoin network, the more robust and decentralized it becomes.
Continue reading: https://cointelegraph.com/bitcoin-for-beginners/what-is-a-bitcoin-node-a-beginners-guide-on-blockchain-nodes

If digital marketers seriously weigh the pros and cons of cryptocurrency-driven digital marketing, they are bound to realize its value and worth.
Cryptocurrency and blockchain technology are steadily being adopted by a growing number of industries. For instance, not only is blockchain used in things like trading and finance but it is even used in healthcare as a way of storing patient data. In the coming years, we will begin to see more cryptocurrency in the digital marketing industry.
Only a small percentage of big businesses have made a firm decision to use cryptocurrency in the near future, but it’s inevitable that many other companies will follow the example set by those who do. But what will crypto’s effects on the market be? And what are the pros and cons of a crypto-driven digital marketing industry?
What Is Digital Marketing?
Digital marketing, otherwise known as online marketing, is advertisement and brand promotion that is carried out through electronic devices. You probably see examples all the time without thinking about it. For example, social media posts, search engine marketing, and display ads are all types of digital marketing.
Modern digital advertisements currently focus on reaching as many people as possible in the hopes of achieving a decent sales conversion rate. This strategy, known as shotgun marketing, is by its nature quite indiscriminate. This might be due to the fact that the intended audience is very large or due to the fact that there is no target demographic at all.
To determine the target market for their product, marketers acquire statistics about the public’s browsing and purchasing habits from private businesses. But without conducting surveys, it’s difficult for businesses to know whether their commercials were successful.
What Effect Does Crypto Have on Digital Marketing?
So, when cryptocurrency is incorporated into digital marketing, what changes can we expect to notice?
Current digital commercials involve four bodies: you, the consumer; the content creator; the advertising team; and whatever platform is hosting the ad, whether that be Google, YouTube, Twitter, et cetera. Crypto-driven marketing eliminates the need for a hosting platform, cutting out the middleman.
Continue reading: https://www.coinspeaker.com/how-cryptocurrency-change-digital-marketing/

The main concern of classical economics revolved around how specialization and exchange make human life better. One of the main advantages of artificial intelligence (AI) lies in enabling further specialization and division of labor. AI processes data to predict and humans use the predictions to make decisions. 
Let us unpack this phenomenon now. 
Humans and technology
Early-generation, or classical, economists were particularly concerned with how the division of labor along the lines of freely chosen specialization allows people to benefit from a society-wide chain of value creation. The father of modern economics, Adam Smith (1723-1790) established that specialization drives surpluses and innovation. David Ricardo (1772-1823) identified how even the least productive members of society could benefit from specialization. And even the angry Karl Marx (1818-1883) saw the advantage of the division of labor. His erroneous qualm was with the capitalist retaining the benefits of the division of labor instead of allowing them to flow to the specialized worker.
Specialization, however, is not restricted to humans. The more technology permeates economic exchange, the more there is a labor division between humans and technology. Instead of weaving by hand, most textile producers use machinery for that task. The machine makes the fabric that has been designed and engineered by people. Instead of doing arduous calculations ourselves, we let the calculator perform the arithmetic of models conceived by humans. The Bloomberg Terminal freed the human analyst from writing quotes on a chalkboard to be able to focus on deciding how to invest. In short, utilizing technology is about finding its specialized employment along the value creation chain. 
Technology enhances the division of labor between humans and machines. It allows each to specialize even further in what they respectively do best. And this comes to the greatest benefit to humans. This division of labor enables them to create novelties, produce more goods and increase quality. By making people able to focus on what they individually do best, specialization and the division of labor enhance their productivity and, along with it, their income and the quality of life.
Continue reading: https://www.gisreportsonline.com/r/ai-prediction/

In 2019 a study published in the journal Science found that artificial intelligence from Optum, which many health systems were using to spot high-risk patients who should receive follow-up care, was prompting medical professionals to pay more attention to white people than to Black people. Only 18% of the people identified by the AI were Black, while 82% were white. After reviewing data on the patients who were actually the sickest, the researchers calculated that the numbers should have been about 46% and 53%, respectively. The impact was far-reaching: The researchers estimated that the AI had been applied to at least 100 million patients.
While the data scientists and executives involved in creating the Optum algorithm never set out to discriminate against Black people, they fell into a shockingly common trap: training AI with data that reflects historical discrimination, resulting in biased outputs. In this particular case, the data that was used showed that Black people receive fewer health care resources, which caused the algorithm to mistakenly infer that they needed less help.
There are a lot of well-documented and highly publicized ethical risks associated with AI; unintended bias and invasions of privacy are just two of the most notable kinds. In many instances the risks are specific to particular uses, like the possibility that self-driving cars will run over pedestrians or that AI-generated social media newsfeeds will sow distrust of public institutions. In some cases they’re major reputational, regulatory, financial, and legal threats. Because AI is built to operate at scale, when a problem occurs, it affects all the people the technology engages with—for instance, everyone who responds to a job listing or applies for a mortgage at a bank. If companies don’t carefully address ethical issues in planning and executing AI projects, they can waste a lot of time and money developing software that is ultimately too risky to use or sell, as many have already learned.
Your organization’s AI strategy needs to take into account several questions: How might the AI we design, procure, and deploy pose ethical risks that cannot be avoided? How do we systematically and comprehensively identify and mitigate them? If we ignore them, how much time and labor would it take us to respond to a regulatory investigation? How large a fine might we pay if found guilty, let alone negligent, of violating regulations or laws? How much would we need to spend to rebuild consumer and public trust, provided that money could solve the problem?
Continue reading: https://hbr.org/2022/07/why-you-need-an-ai-ethics-committee

Social media is experiencing significant growth each year, supported by the rapid advancement of digital technologies. According to the findings of 2022 Hootsuite research, 4.62 billion users around the world are active on social media, which is about a 10% increase over the last year. As social media continues to evolve, the number of users who create, share and exchange content online is also rising.
This has resulted in a huge surge of user-generated content as a new way of publishing information, engaging in online communities and discussions and participating in social networking. According to study results from Polaris Market Research, the global user-generated content platform market was worth over $3 billion in 2020, with projections to grow at a CAGR of 27.1%, reaching more than $20 billion by 2028.
Challenges Of Content Moderation
The ongoing increase in user-generated content makes it difficult for human moderators to deal with big volumes of information. The challenge to manually check for online content becomes even more immense for moderators as social media changes the expectations of users, who might be more demanding and less tolerant toward online content sharing rules and guidelines. Furthermore, the risk of constantly exposing human moderators to distressing content can make manual moderation significantly unpleasant. This is where AI-powered content moderation comes in.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/14/the-growing-role-of-ai-in-content-moderation/?sh=1ed08a4e4a17

Think of your favorite movie as a kid, say in the first 10 years of your life. Now think of your favorite movie from the past decade. Do you have one? Do you have 100?
In a world with basically infinite content, choice is one of our greatest joys—and frustrations. With each passing year, consumers seem to grow more fickle and demanding, regularly moving to the platforms and publications that offer not only the best catalog but also the best customer service, content experience, user interface, and bang for the buck.
And even these features may not be enough, as the recent upheaval among the major streamers has shown.
Holding on to viewers, readers, and listeners has become more important than ever. Yet most consumers can only maintain so many subscription services at once. The goal for media companies needs to be to sustain their interest, and with as much share of the consumer’s wallet as possible.
As such, churn is now the most prominent enemy of the media and entertainment industry business model. Consumers can be mercurial, sensitive to price and changes in content catalogs. Just as adding a service has rarely been easier, so is dropping one, which consumers have shown themselves more than willing to do when a channel is no longer serving their needs.
With these challenges front and center, leading media and entertainment companies are increasingly turning to data analytics and personalized content recommendations to improve customer experience and retention. In the dog-eat-dog digital world, it's no longer the loudest bark that gets the most attention. It's about pairing the right breed to the sensibilities of a specific person, and having the best stable of information and offerings to make that match and keep it going.
Continue reading: https://www.forbes.com/sites/googlecloud/2022/06/13/churn-it-down-how-media-companies-can-use-ai-to-keep-and-win-subscribers/?sh=62806b873744

There are plenty of organizations that are dabbling with AI, but relatively few have decided to go all in on the technology. One that is decidedly on that path is Mastercard. Employing a combination of acquisitions and internal capabilities, Mastercard has the clear objective of becoming an AI powerhouse. Just what does that term mean, and how is it being applied at the company?
What’s an AI Powerhouse?
Some refer to the idea of aggressive, pervasive adoption of AI as being “AI first.” Others use the term “AI fueled” or “all in on AI” (that’s Tom’s favorite, since it’s the title of his forthcoming book on the subject). Mastercard prefers “AI powerhouse.” Regardless of the descriptor, the concept refers to organizations that apply AI throughout their businesses, using it to either transform operations or develop new products, services, and business models, or both. These companies employ multiple AI technologies, develop many use cases, and put them all into production deployment.
As we’ve noted in previous columns, this level of engagement is unusual. In a 2019 MIT Sloan Management Review and Boston Consulting Group AI survey, 65% of respondents said they hadn’t seen value from their recent AI investments, in part because relatively few projects had been put into production. Survey respondents reported being skittish about the technology, with 45% saying they perceived some risk to their business from AI (up from 37% two years earlier).
To succeed in becoming an AI powerhouse, companies need to have a set of prerequisites in place. Senior leaders of the organization have to be on board and engaged with the effort because AI use cases must enable new ways of doing business and AI powerhouses inevitably invest at least a fair amount in AI. A lot of high-quality data is needed because that’s how machine learning models are trained. From a talent perspective, companies need smart individuals who can develop and apply AI systems. And it’s important that an organization have an ethical compass about how it uses AI and other information resources.
Continue reading: https://sloanreview.mit.edu/article/becoming-an-ai-powerhouse-means-going-all-in/

U.S. inflation has hit a 40-year high, leaving businesses scrambling for ways to combat diminishing profit margins. Some have been quick to pass the buck onto consumers by increasing prices, or by reducing the size of products (a practice known as "shrinkflation"). But for many, offloading increasing costs by these methods is a surefire way to drive away business. As scrappy businesses seek to defy inflation, artificial intelligence has the answer: Efficiency. 
With a focus on efficiency, businesses are able to do more with what they have. Because consumers shouldn't be the only ones looking to save money. Businesses should too. 
To save money, you need to start by improving efficiency. In AI, efficiency means optimizing operations with precise forecasting, predictive maintenance, quality control and risk reduction. But it also means identifying and correcting areas of inefficiencies that cost companies. It increases productivity and maintains profit margins amid increasing costs. Simply put, it saves you money. 
According to an analysis by Boston Consulting Group, AI can reduce conversion costs by up to 20 percent, with up to 70 percent of the cost reduction resulting from higher workforce productivity. But AI is also expensive, time-consuming and out of the question for many small businesses and bootstrapped startups. The good news is that startups and small businesses can use big data--without AI--by leveraging the fundamental strategies behind data science. 
Continue reading: https://www.inc.com/magazine/202203/steven-i-weiss/tope-awotona-calendly-meetings-productivity.html

The long-awaited drones from Amazon (AMZN) are finally making their debut in California to deliver packages for the online retailer's customers.
Amazon Prime members who live in Lockeford, California, will be the first customers to receive their deliveries from a Prime Air drone. A start date on when the deliveries would begin was not given by the company.
The internet behemoth has been working on developing and creating the drones for its delivery service for nearly a decade, the company said in a blog post on June 13.
Customers can expect deliveries for free in under an hour from Prime Air.
"The promise of drone delivery has often felt like science fiction," the company wrote. 
The company has been working on how to deliver packages safely and efficiently on a large scale after developing two dozen prototypes.
Building a network that is able to deliver packages across many miles in various communities has remained a challenge for drone companies, including Amazon, the company said in the blog post.
"Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that — and later this year, Amazon customers living in Lockeford, California, will become among the first to receive Prime Air deliveries," the company said
Amazon's Prime Air will be able to deliver thousands of everyday items, but the company did not provide any details on which ones. Packages will be delivered in the backyards of homes in 2022, the company said.
Customers will place their orders online and will receive an estimated arrival time.
Continue reading: https://www.thestreet.com/technology/amazon-says-drones-are-finally-ready-to-fly

Zamokuhle Aja-Okorie‘s unique experience is influenced by German nuns who taught her to be a bold individual. Now, she is a South African impact entrepreneur, who owns OAO Investments, a novel entrepreneurial company driven by a Pan-African vision and an intrinsic commitment.
In this edition of Technext’s series on women in tech, we spoke to Zamokhule Aja-Okorie, and her plans for the future. 
The Beginning
Aja-Okorie had her primary education under the disciplined watch of German Nuns in South Africa. After her stint with the Nuns, she attended Parktown High School For Girls, where she was placed on the front line of leadership and they reinforced that there is enormous potential and power in being a girl. 
Aja-Okorie continued to the University of Pretoria and studied for a BA in Psychology. After getting her first degree, she went on to pursue her dream of touring the world and getting paid for it; as a flight attendant.

I became a flight attendant for three years to tick off my childhood dream of seeing the world and getting paid to do that. If I were in my 20s in these times I would have probably been a travel influencer. After I had done it for three years, I realized the lifestyle isn’t very suited to me, so I moved from South African Airways to working in Hospitality, Marketing and PR, Infrastructure, Technology, Healthcare, Investor Relations, Chemicals and Mining.

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Finding purpose through Tech

The very evolution of humankind is dominated by technological leaps which has changed the face of the modern world. As a result of these leaps I had no choice in getting into technology but was automatically placed in it like most people.

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Continue reading: https://technext.ng/2022/06/13/i-felt-strangled-and-knew-i-couldnt-continue-how-zamokhule-aja-okorie-found-purpose-through-tech/

Former Twitter CEO Jack Dorsey recently announced his vision for a new decentralized web platform that is being called Web 5.0 and is being built with an aim to return “ownership of data and identity to individuals”. What is Web 5.0, and how will it be different from Web 3.0 and Web 2.0?
What do the terms Web 1.0, Web 2.0 and Web 3.0 mean?
Web 1.0 was the first generation of the global digital communications network. It is often referred to as the “read-only” Internet made of static web-pages that only allowed for passive engagement.
The next stage in the evolution of the web was the “read and write” Internet. Users were now able to communicate with servers and other users leading to the creation of the social web. This is the world wide web that we use today.
Web 3.0 is an evolving term that is used to refer to the next generation of Internet – a “read-write-execute” web – with decentralization as its bedrock.
It speaks about a digital world, built leveraging the blockchain technology, where people are able to interact with each other without the need of an intermediary. Web 3.0 will be driven by Artificial Intelligence and machine learning where machines will be able to interpret information like humans.
Continue reading: https://indianexpress.com/article/explained/everyday-explainers/what-is-web-5-0-blockchain-powered-digital-network-twitter-ex-ceo-7967663/