Apple's New iOS Could Cut Audience Network Ad Revenue In Half for Facebook

 

Online advertising has changed drastically over the last few years, moving from cookies which people could easily erase to device ID number which of course are unique. This evolution has allowed Facebook to refine its Audience Network advertising model with better targeting and specific clusters. 

This of course presuppose that device ID number are both linked to Individual Identities but somehow not private, a legal oxymoron. This is what Apple is planning to change with the release of its next iOS platform following the iPhone 12 later this year which will require consent from users... for every application! 

This is a master stroke from Apple to protect privacy and a mortal danger for Facebook, endangering the essence of its business model. But who said the 5 giants would coexist very long in the current ecosystem?

The article below is from Zero Hedge

Typically, it is media companies that cower in fear any time Facebook changes its new algorithm, terrified it could result in a catastrophic drop in ad revenues. Now, it's Facebook's turn to be at the mercy of its most popular platform, in this case Apple's iOS operating system, whose new upcoming version iOS 14 could lead to a more than 50% drop in Facebook's Audience Network advertising business, the company admitted in a blog post today.

While previously Facebook had warned that iOS 14 could impact its advertising business, only today did the company outline just how profound that impact could be. The Facebook Audience Network allows mobile software developers to provide in-app advertisements targeted to users based on Facebook’s data.

In today's post-cookie world, advertisers use a unique device ID number called the IDFA to better target ads and estimate their effectiveness CNBC explains. However, in iOS 14, each app that wants to use these identifiers will ask users to opt in to tracking when the app is first launched. Facebook said its apps will not collect IDFA information on iOS 14.

The impact of the revision could be tremendous: according to Facebook, more than 1 billion people see at least one Audience Network ad every month, although many of those are probably using Android phones and will not be affected by the change. While Facebook derives virtually all revenue from advertising, it’s not known what percentage is attributable to the Audience Network versus ads on Facebook and other properties.

As CNBC adds, in Facebook's blog post it outlined steps it will take to ensure its advertising business is in compliance with Apple’s requirements. These steps will limit how effectively Facebook and its advertisers can target ads to iPhone and iPad users.

“We know this may severely impact publishers’ ability to monetize through Audience Network on iOS 14, and, despite our best efforts, may render Audience Network so ineffective on iOS 14 that it may not make sense to offer it on iOS14 in the future,” Facebook said in a blog post.

“While it’s difficult to quantify the impact to publishers and developers at this point with so many unknowns, in testing we’ve seen more than a 50% drop in Audience Network publisher revenue when personalization was removed from mobile ad install campaigns,” Facebook said. “In reality, the impact to Audience Network on iOS 14 may be much more, so we are working on short-and long-term strategies to support publishers through these changes.”

 Apple has not said when iOS 14 will launch, but it’s expected to roll out this year.

 

The Secret of AI is People

 

A great article from Harvard Business Review on how to integrate AI in a company. This should be compulsory reading at many board meetings. AI is a moving target so understanding what exactly it can do for your organization may be illusive. But understanding how to integrate it within a company is not only possible but a necessity. Within a short few years the gap between companies who have done it successfully and the rest will be unbridgeable. 

 

Too many business leaders still believe that AI is just another ‘plug and play’ incremental technological investment. In reality, gaining a competitive advantage through AI requires organizational transformation of the kind exemplified by companies leading in this era: Google, Haier, Apple, Zappos, and Siemens. These companies don’t just have better technology — they have transformed the way they do business so that human resources can be augmented with machine powers.

How do they do it? To find out, we conducted a multistage study over five years, beginning with a survey of senior managers and executives, followed by interviews and surveys across a wide range of industries to identify technology implementation strategies and barriers, and in-depth studies of five leading organizations. Our key takeaway is counterintuitive. Competing in the age of AI is not about being technology-driven per se — it’s a question of new organizational structures that use technology to bring out the best in people. The secret to making this work, we learned, is the business model itself, where machines and humans are integrated to complement each other. Machines do repetitive and automated tasks and will always be more precise and faster. However, those uniquely human skills of creativity, care, intuition, adaptability, and innovation are increasingly imperative to success. These human skills cannot be “botsourced,” a term we use to characterize when a business process traditionally carried out by humans is delegated to an automated process like a robot or an algorithm.

How do leaders get the most out of AI?

From our research we have developed a four-layer framework that shows organizational leaders how they can create a human-centric organization with super-human intelligence. The four layers are not “steps,” which would imply a sequential progression. The four layers of intentionality, integration, implementation, and indication (the Four I model) must be stacked all together, or else the use of AI will fail to deliver a sustainable competitive advantage. Here’s how it works.

The first layer of the Four I model is intentionality of purpose, beyond the mere pursuit of profits. An intentional organization knows why it matters to the world, not just its shareholders. A good example of intentionality in the use of AI comes from Siemens, which evolved from a shareholder-profit-maximizing power generation and transmission company into a leading provider of electrification, automation, and digitalization solutions with energy-efficient, resource-saving technologies driven by AI and the Internet of Things (IoT) in service to society. This cultural shift toward a higher human-centric purpose impacted not just marketing and product design but also the strategic decision to, as Scott D. Anthony, Alasdair Trotter, and Evan I. Schwartz wrote for HBR, “divest its core oil and gas business and redeploy the capital to its Digital Industries unit and Smart Infrastructure business focused on energy efficiency, renewable power storage, distributed power, and electric vehicle mobility.” While financial performance and shareholder value will always be important, creating human-centered, technology-powered organizations will actually drive financial performance in the age of AI.

To that end, Siemens is launching a combination of hardware and software that enables AI throughout its Totally Integrated Automation (TIA) architecture, an approach that aligns Siemens’ mission with its AI strategy. The TIA architecture uses AI as a bridge that spans from corporate headquarters out to industrial end users. Siemens’ proprietary “MindSphere” is a cloud-based IoT operating platform that reaches into Siemens’ industrial user-operated controller and field device products. The MindSphere’s neural processing unit module allows human users to benefit from Siemens’ in-house AI capabilities, while also enabling human users to impart their own experience to train the machines. According to Siemens Factory Automation specialist Colm Gavin, “With artificial intelligence we are able to train, recognize, and adjust to allow more flexible machinery. Because, do we want 10 machines to package 10 different types of products, or a tool that accommodates different packages and different sizes and automatically adjusts to the new format?” Smarter machinery with TIA architecture leverages AI to advance the company’s intentionality, while increasing flexibility, quality, efficiency, and cost-effectiveness for its end users.

Alternatively, a negative example of the relationship between intentionality and AI is illustrated by recent issues confronting Facebook. Facebook’s mission, “to give people the power to build community and bring the world closer together,” sounds noble. Yet recent use of its AI has raised concerns from advertisers and civil rights groups alike. The social media giant has struggled to align its mission with its use of AI that seems to have the opposite effect: Facebook’s content “feed” is driven by algorithms that prioritize inflammatory, misleading, and socially divisive content. Facebook’s use of AI seems to drive social division, which is antithetical to its purpose as a social media company, and is having financial consequences. Because its algorithms have promoted disinformation, violence, and incendiary content, major advertisers are now cutting ties with Facebook, dealing a strong blow to the company that derives 98% of its income from ad revenue. Some of the largest brands in the world, including Coca-Cola and Unilever, pulled advertisements from Facebook for promoting content antithetical to their brand’s values, resulting in a one-day drop of 8.3% in market value, or $56 billion.

The second layer of the Four I model is integration of human and AI resources across the organization. To lead in the technology era, companies must shift away from silos to organizational structures with flexible teams that integrate people horizontally and vertically, from product creation to strategic decision making. As one executive we spoke with explained, before the AI shift, it was necessary for workers to have deep knowledge of a narrow area. Today, deep analytical content can come from AI. What is needed is the ability of workers to synthesize information, which means collaborating across functions and working in cross-functional teams. To foster innovation and adaptability, organizations need to transition from rigid hierarchies to flexible, agile, and flatter structures. Google, Haier, and Zappos may have differences in their organizational structures, but the common elements are flatness and fluidity. The recommended structure is more like a playground for smart, talented people to generate customer-centric products. Employees have fluid roles in cross-functional teams around problems as opposed to individual roles and responsibilities. These teams spontaneously form when problems arise, then dissolve when the work is done, reallocating human resources as needed.

The other side of this — which can easily be forgotten — is that human and AI teams should also be structured in an integrated manner. This allows humans to transcend their ordinary cognitive limitations, without placing unreasonable reliance on a robot to perform human tasks that require high degrees of care and skill. An example comes from the medical context, where AI offers tremendous potential not as a substitute for, but as a supplement to, physician-driven care. Recent research in the journal Nature found that, “good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone.” This means high-stakes, highly-skilled human decision-making can benefit from AI so long as it is integrated properly within the human decision-making context.

The third layer of the Four I model is implementation. Implementation requires engaging human talent, tolerating risk, and incentivizing cross-functional coordination. An executive at a large pharmaceutical we spoke with said, “you have to get people to believe in the technology.” We saw this in another of the companies we spoke with when we learned that despite having integrated AI, managers were modifying the output values from the algorithm to fit their own expectations. Others in the same company would simply follow the old decision-making routine, altogether ignoring the data provided by algorithms. Therefore, human behavior is central to implementing AI.

Top performing companies spent significant time communicating with employees and educating them, so that the human talent understood how machines made their jobs easier, not obsolete. To build trust in AI, it is imperative for leaders to communicate their vision transparently, explaining the goal, the changes needed, how it will be rolled out, and over what timeline. Beyond communication, leaders can inoculate their workforce against fear of AI by arranging for visits to other companies that have undergone similar transformations, providing a model for workers to see with their own eyes how the technology is used.

We saw many approaches to this in our research. Pilot projects where technology is rolled out in a limited scope give workers some ownership over the adoption process. Giving workers an opportunity to tinker with the technology before a final adoption decision is made eases the transition. Financial services firm Capital One even created an internal training institute called Capital One University that offers professional training programs to promote a broader understanding of analytics throughout the organization’s culture.

The fourth layer of the model is indication or performance measurement. Ultimately, success and progress need to be measured, and leading companies have moved from traditional productivity measures to aspirational metrics. Using the right indicators can drive improvements and help a business focus on what they deem important. Aspirational metrics that incentivize innovation and creativity encourage employees to exercise those uniquely human traits. The lesson is to be careful what you measure. Monitoring the wrong performance indicator has a strong tendency to lead to the proverbial tail wagging the dog. Humans are clever, and if incentives are not properly aligned with intelligently designed performance metrics, human workers will resort to lazy, clever, and cynical hacks to game the system, maximizing the appearance of performance under one measure while actually failing to deliver the output that management was actually hoping for when they implemented that measure.

Most companies use KPIs, but in our research we saw that successful companies more often used Objectives and Key Indicators (OKRs). What we learned was that KPIs by themselves don’t encompass strategic and ambitious goals needed in the age of AI and they don’t motivate to reach for the sky. The goal of OKRs is to precisely define how to achieve ambitious objectives where failure is imminently possible, through concrete, measurable specifications. They encourage creative, novel, and aspirational performance by showing progress toward a goal even if the goal itself is unattainable. Google famously started using OKRs in 1999; a change some even credit as a critical element of Google’s success. At Google, OKRs have helped develop transparency. Everybody knows the company’s goals, what everyone is doing, how they have done in the past, the trajectory they are on, and how they are getting to where they want to go.

Building Companies on Super-human Intelligence

Our research shows that AI is so much more than just the latest incremental improvement in existing technology, however deploying it effectively takes leadership and coordination across all sectors of a company. Unlocking the full potential of an organization’s human resources by adopting AI strategically requires revisiting the very structure of the company and how it measures its progress toward fulfilling its mission. These issues are core issues to the identity of a company and modifications here are fraught with insecurity and risk, but this is a risk needed to compete in the age of AI. Intentionality, integration, implementation, and indication must be layered in order to create a human-centric enterprise governed by super-human intelligence. Achieving this requires talent at all levels to have systems-thinking, understand how the work being done meshes with that of others elsewhere in the organization, how it meets customer needs, and how it impacts the company’s strategy and financial picture. By following the Four I model, companies can unlock super-human intelligence without losing the human touch.

We were surprised to discover how few organizations have unlocked this secret. But we were encouraged by the progress of the ones that had. With this model, we hope, more companies can create the conditions for realizing super-human intelligence and performance, delivering sustainable competitive advantages in the age of AI.

Covid-19 compared to previous pandemics (infographic)

 

Here's a good infografics from Visual Capitalist to visualize Covid-19 in relation to other pandemics which have preceded it. 

It still has "room" to grow since the pandemic is on-going. But even multiplied by 3 or 4 it would remain a rather minor one historically. And that is without questioning underlying factors such as co-morbidity which further reduce its potential size. (Most people affected are elderly who almost always have other illnesses which in many cases may be the real cause of death.)   

The one graphic missing in this infographic is the number of death relative to total population. This is important because global population has been expanding fast over the last century, reducing further the relative impact of recent pandemics. 

The infographic and relevant comments can be found below:

Visual Capitalist

 

 

Personally, I do believe that governments around the world are being manipulated not openly and not with their knowledge but manipulated nevertheless. I do not believe it is a "conspiracy" as such but I am open to the possibility considering the financial and systemic risks our society is facing.

This article argues otherwise, that governments are "out of their depth" and just imitate each other to minimize risk (for themselves of course, not for the population!) There is a fair possibility that this is the case which is why I re-publish it. The arguments are solid and well supported. 

Authored by Jeffrey Tucker via The American Institute for Economic Research,

Governments Are Faking It, and Copying Each Other

A mystery for months is how it is that so many governments in so many different places on earth could have adopted the same or very similar preposterous policies, no matter the threat level of the virus, and without firm evidence that interventions had any hope of being effective. 

In the course of two weeks, traditional freedoms were zapped away in nearly all developed countries. In a seriously bizarre twist, even the silliest policies replicated themselves like a virus in country after country. 

For example, you can’t try on clothing in a store in Texas or in Melbourne, or in London or in Kalamazoo. What’s with that? We know that the COVID bug is least likely to live on fabrics unless I have symptoms of it, sneeze on my handkerchief and then I stuff it in your mouth. The whole thing is a ridiculous mysophobic overreach, like most of the rules under which we live. 

Then there was the inside/outside confusion. First everyone was forced indoors and people were arrested for being outdoors. Later, once restaurants started opening, people were not allowed indoors so eating establishments scrambled to make outdoor dining possible. Are we supposed to believe that the virus lived outside for a while but then later moved inside? 

Or these curfews. So many places have them despite a complete absence of evidence that COVID spread prefers the night to the day. I guess the real point is to put a stop to revelry that might bring people together in a fun way? It’s like all our governments decided on the same day that COVID spreads through smiles and fun, so we have to banish both. 

In Sydney and Los Angeles, and also in Detroit and Miami, you need to wear a mask when you walk in a restaurant but not when you sit. And this 6-foot rule is highly suspect too. It seems to imply that if you get too close to each other, COVID spontaneously appears. At least people seem to believe that. 

Australia, in its way, even created a slogan and a jingle to go with it. “Staying Apart Keeps Us Together,” says Orwell, I mean, Victoria. 

Socially distance! Don’t be a silent spreader! Even though the largest study yet has shown that “asymptomatic cases were least likely to infect their close contacts.” Which is to say, this is mostly nonsense. 

In most places too, you have to quarantine two weeks when you arrive from afar, even though it is rare that the virus incubation period is that long. The mean period is 6 days, perhaps, which is what one would expect from a coronavirus like the common cold. 

Oh, and in department stores, you can’t spray perfume to try it out, because surely that spreads COVID – not. Except that there is not one shred of evidence that there is any truth to this. This one seems completely made up, though it is widely imposed. 

The list goes on. The bans of gatherings over 50 outdoors and 25 indoors, the closures of gyms at a time when people need to be getting healthy, the shutting of theaters and bowling alleys but the keeping open of big-box stores – these policies are as ubiquitous as they are unsupported by any science. And we’ve known this for many months, ever since the media meltdown over Florida Spring Break ended up in zero fatal cases contracted at the revelry. 

The worst case is school closings. They were shut down at the same time all over the world, despite evidence available since at least January that the threat to children is nearly zero. Yes, they do get COVID almost entirely asymptomatically, which is to say they do not get “sick” in the old-fashioned sense of that term. What’s more, they are highly unlikely to spread it to adults precisely because they do not have symptoms. This is widely admitted. 

Still governments decided to wreck kids’ lives for an entire season. 

And the timing of it all seems strangely suspicious. All these countries and states implemented this compulsory clown show at the same time, whether cases were everywhere or nowhere. 

In the U.S., this was fascinating to watch. The shutdowns happened all over the country. In the Northeast, the virus had already spread widely toward herd immunity. The South shut down at the same time but the virus wasn’t even there. By the time the virus did arrive, most states in the South had already reopened. The virus doesn’t seem to care either way. 

Now, looking at this it is very easy to go to conspiracy as the explanation. There is probably some secret hand at work somewhere that is guiding all of this, the thinking goes. How can so many governments in the world have simultaneously lost their marbles and abolished the people’s liberties in such a cruel way, while trampling on all rights of property and association?

I tend to resist big conspiracy theories on this subject simply because I seriously doubt that governments are smart enough to implement them. From what I can see, these governors and statesmen seem to be making things up in a crazy panic and then sticking with them just to pretend that they know what they are doing. 

Pete Earle’s theory of pot commitment seems to explain why the stringency persists even in the lack of evidence that they do anything to suppress the virus. 

But how can we account for the imposition of so many similarly ridiculous rules at the same time across so many parts of the globe? 

I invite you to examine a very interesting study published by the National Academy of Sciences: Explaining the homogeneous diffusion of COVID-19 nonpharmaceutical interventions across heterogeneous countries. 

A clearer title might be: how so many governments behaved so stupidly at once. The theory they posit seems highly realistic to me: 

We analyze the adoption of nonpharmaceutical interventions in the Organisation for Economic Co-operation and Development (OECD) countries during the early phase of the coronavirus disease 2019 (COVID-19) pandemic. Given the complexity associated with pandemic decisions, governments are faced with the dilemma of how to act quickly when their core decision-making processes are based on deliberations balancing political considerations. Our findings show that, in times of severe crisis, governments follow the lead of others and base their decisions on what other countries do. Governments in countries with a stronger democratic structure are slower to react in the face of the pandemic but are more sensitive to the influence of other countries. We provide insights for research on international policy diffusion and research on the political consequences of the COVID-19 pandemic.

This seems to fit with what I’ve seen anecdotally. 

These guys in charge are mostly attorneys with specializations in bamboozling voters. And the “public health authorities” advising them can get credentials in the field without ever having studied much less practiced medicine. So what do they do? They copy other governments, as a way of covering up their ignorance. 

As the study says:

While our paper cannot judge what an “optimal” adoption timing would be for any country, it follows, from our findings of what appears to be international mimicry of intervention adoptions, that some countries may have adopted restrictive measures rather sooner than necessary. If that is the case, such countries may have incurred excessively high social and economic costs, and may experience problems sustaining restrictions for as long as is necessary due to lockdown fatigue. 

Which is to say: the closures, lockdowns, and imposed stringency measures were not science. It was monkey see, monkey do. The social psychology experiments on conformity help explain this better than anything else. They see some governments doing things and decide to do them too, as a way of making sure they are avoiding political risk, regardless of the cost. 

All of which only increases one’s respect for the governments around the world that did not lock down, did not close business, did not shut down schools, did not mandate masks, and did not push some crazy kabuki dance of social distancing in perpetuity. South Dakota, Sweden, Taiwan, and Belarus come to mind. It takes an unusual and rare level of incredulity to avoid this kind of herd mentality. 

Why did so many governments go so nuts at once, disregarding their own laws, traditions, and values by bludgeoning their own people with the excuse of science that has turned out to be almost completely bogus? Some people claim conspiracy but a much simpler answer might be that, in their ignorance and stupor, they copied each other out of fear.

Sakoku - Japan closes its doors to foreigners

 

Japan is an Island country and as such, there is a long tradition of  being closed to foreigners called "sakoku". It is therefore no surprise that with the Covid-19 crisis, Japan finds itself at the very front of the most extreme reactions to the pandemic in the world with an almost complete isolation on par with far away Pacific islands. 

But for how long can a nation of 126 million people that imports 60% of its food and exports most of its factories' high-tech output abroad stay closed?

 

Submitted by Christopher Dembik of Saxobank

https://www.zerohedge.com/markets/what-nation-cut-rest-world-looks

Earlier this morning, there has been a couple of Japanese data releases. Japanese consumer price inflation was unexciting with a rate at 0% YoY. While we see some relative price changes in many countries, the basic story for the moment is that inflation will remain low in most countries. In addition, Japan National Tourism Organization has published its latest data regarding the flow of foreign visitors in July. Basically, it shows what a nation cut off from the rest of the world looks like.

The flow of foreign visitors in Japan published by Japan National Tourism Organization is out this morning.

The country was supposed to welcome an unprecedented number of Olympic fans from all around the world just about now, but the pandemic has turned everything upside down.

Arrivals of foreign visitors plunge 99% YoY in July, at 3,800 individuals (slightly up compared to the previous month, when it stood at 2,600 individuals). For the sake of comparison, at the beginning of the year, the country recorded more than 2.6 million foreign visitors in a month’s time.

Whilst the country expected to draw around 40 million visitors this year, the final number for 2020 might fall to 7-8 million at best, which would represent a drop of 80% compared to the target. Over the past years, the contribution of travel and tourism to GDP has significantly increased, to reach 7% in 2019, on the back of government’s incentives to promote foreign tourism via marketing push overseas and eased visa requirements.

The COVID-19 constitutes a serious setback for the government’s hopes for tourism and it is unlikely that the recent campaign to spur domestic tourism launched on July 22 will offset losses generated by the drop in the flow of foreign visitors. Considering the number of new COVID-19 cases has sharply increased since mid-July and that many countries at global level are facing the acute risk of second wave, the country is not expected to reopen to foreigners anytime soon and will probably postpone initial plans to let foreign students and businessmen return.

Like Japan, many other countries has decided to close borders to fight against the spread of the virus, thus hitting hard the tourism sector. At the start of the pandemic, many economists underestimated the negative ripple effect on tourism.

Submitted by Christopher Dembik of Saxobank

Earlier this morning, there has been a couple of Japanese data releases. Japanese consumer price inflation was unexciting with a rate at 0% YoY. While we see some relative price changes in many countries, the basic story for the moment is that inflation will remain low in most countries. In addition, Japan National Tourism Organization has published its latest data regarding the flow of foreign visitors in July. Basically, it shows what a nation cut off from the rest of the world looks like.

The flow of foreign visitors in Japan published by Japan National Tourism Organization is out this morning.

The country was supposed to welcome an unprecedented number of Olympic fans from all around the world just about now, but the pandemic has turned everything upside down.

Arrivals of foreign visitors plunge 99% YoY in July, at 3,800 individuals (slightly up compared to the previous month, when it stood at 2,600 individuals). For the sake of comparison, at the beginning of the year, the country recorded more than 2.6 million foreign visitors in a month’s time.

Whilst the country expected to draw around 40 million visitors this year, the final number for 2020 might fall to 7-8 million at best, which would represent a drop of 80% compared to the target. Over the past years, the contribution of travel and tourism to GDP has significantly increased, to reach 7% in 2019, on the back of government’s incentives to promote foreign tourism via marketing push overseas and eased visa requirements.

The COVID-19 constitutes a serious setback for the government’s hopes for tourism and it is unlikely that the recent campaign to spur domestic tourism launched on July 22 will offset losses generated by the drop in the flow of foreign visitors. Considering the number of new COVID-19 cases has sharply increased since mid-July and that many countries at global level are facing the acute risk of second wave, the country is not expected to reopen to foreigners anytime soon and will probably postpone initial plans to let foreign students and businessmen return.

Like Japan, many other countries has decided to close borders to fight against the spread of the virus, thus hitting hard the tourism sector. At the start of the pandemic, many economists underestimated the negative ripple effect on tourism.