Facebook and Google have recently being getting flack from users for hosting fake news stories. As Jack Nicas and Deepa Seethataman report, “Google and Facebook Take Aim at Fake-News Sites”
Facebook Inc. and Alphabet Inc.’s Google announced steps to prevent fake-news websites from generating revenue through their ad-selling services, signs that technology companies are moving to address a growing controversy about misinformation on the internet.
The Fake News Game is illustrated in Figure 1, and players’ objectives, actions, and tensions are described briefly below.
I recently published a blog entry on the Net Neutrality Game. However, I just found out that there is a critical aspect of the net neutrality issue that I failed to understand, namely that involving deep packet inspection (DPI). Using DPI methods, Internet providers have the capabilities of detecting not only the size of files passing through their lines, but also the content as well. Clearly, there is a world of difference between managing flows of traffic based solely on file size, and managing flows of files based on the type and content of the files.
This analysis considers how the US healthcare system would change if we were to transition from the current multi-payer system to a single-payer system. The analysis first presents facts that will be important in considering what a single-payer system might look like. Then, given these facts, the analysis considers specific issues about the transition.
Facts
1. Four factors affect a person’s risk of premature death.
Behavior, genes, environment, and healthcare services are the four factors that Impact people’s risks of premature death (Kaiser Family Foundation) (see Figure 1).
Figure 1
(i) Behavior: 40%
From Kaiser Family Foundation: “Health behaviors, such as smoking and diet and exercise, are the most important determinants of premature death.”
According to OECD, “Health at a Glance 2015”
While genetics is a risk factor, only about 5% to 10% of all cancers are inherited. Modifiable risk factors such as smoking, obesity, lack of exercise and excess sun exposure, as well as environmental exposures, explain up to 90-95% of all cancer cases.
(ii) Genes: 30%
(iii) Social and Environment: 20%
Figure 2 (from Kaiser Family Foundation) displays specific social and environment factors contributing to health.
Figure 2
More from the OECD report:
Recent analysis shows that, although overall spending on social services and health care in the United States is comparable to other Western countries, the United States disproportionately spends less on social services and more on health care.
(iv) Health Care: 10%
Current Doctor-Patient Communications Involve Miscommunications
Suppose a patient damages his knee. He goes to see an Orthopedic Surgeon. The surgeon conducts some tests and concludes that the patient has torn his meniscus and needs arthroscopic surgery to fix it (see Figure 1)
Figure 1
Source:http://www.newhealthguide.org/Meniscus-Surgery-Recovery-Time.html
After informing the patient of this, the patient then asks the surgeon, “How much will this surgery cost me?”
The surgeon replies to the patient’s question with something akin to, “I have no idea,” or “I can’t tell you.”
That simple statement goes a long way towards killing the patient’s trust of the doctor. And without trust, patients are less likely to comply with the doctor’s recommendations, which, in turns leads to worse patient outcomes, less satisfied patients, fewer patient referrals, and more billing disputes.
And all this happens due to a miscommunication between the surgeon and the patient.
The Trump Administration's most recent proposal to prevent terrorists from entering the country is to undertake "extreme vetting" in the form of disclosing contacts on their mobile phones, social-media passwords and financial records, and answering probing questions about their ideology.
This brings to mind the nature of the more general Terrorist Screening Game, in which The Government establishes rules and procedures for Screeners to follow in an attempt to weed out Terrorists from Non-Terrorist Visitors and Immigrants into the country.
This analyzes examines the objectives of players in the Terrorist Screening Game and considers relevant questions and issues.
The 4 C’s of Diamonds
Diamond Database
Analysis of Diamond Prices
“Better a diamond with a flaw than a pebble without one.”
-- Chinese Proverb
Mapping apps, such as Waze and Google Maps, have created enormous value for users by helping them get to where they’re going faster. As least initially, when few people were using mapping apps, the apps were particularly helpful for individual users in rerouting them around traffic problems. However, now that a large portion of drivers has adopted mapping apps, we’re seeing problems with side routes becoming congested, as everyone is being rerouted through the same detours. So not only is there congestion on the original route -- from where drivers have been re-routed – but there is now congestion in many more additional locations in society – to where drivers have been re-routed.
It turns out that mapping apps are most beneficial to users for dealing with congestion problems when only a few users have adopted them. But they become less useful to users as more people adopt them. That is, the mapping apps exhibit negative network externalities for users when it comes to congestion. At the same time, as more people adopt mapping apps, other members of the community – those who live on the routes through which mapping app users are being re-routed – also suffer, yet another negative externality.
What we have is a game:
- Providers of mapping apps want as many Users as possible to adopt
- Users of mapping apps want as few Users as possible to adopt
- Local Drivers want as few Users as possible to adopt
- Freeway Drivers are happy if Users of mapping apps divert to local roads, if it reduces congestion on the freeway.
This analysis examines mapping apps and other types of resource allocation games.
A recent article in the NYT, “Weighty Choices, in Patients’ Hands” by Laura Landro, discussed the difficult choices patients face in making healthcare decisions, as treatment options become more complex. Due to the overwhelming nature of the information and the inability of physicians to provide patients with the ins and outs of all their options, some medical services providers are providing patients with “coaches” to help educate them about the upsides and downsides of all the patients’ choices and to help guide them in preparing relevant questions for the patients’ doctors. In the excerpt that follows, I’ve highlighted in blue the results reported in the article for this new patient education process.
In an earlier analysis, I looked at some of the dynamics involved in Playing the Online Adblocking Game
This analysis examines the dynamics involved in the Online Adblocking Game, which includes such players as Online Users, Content Providers, Advertisers, and Adblock Software and Services Providers. The first part of the analysis will examine trends in online ad revenues and ad pricing models, as a backdrop for analysis of the Adblocking Game. The second part of the analysis will introduce adblocking and describe its use. And the third part of the analysis (or perhaps third and fourth) will discuss the adblocking game.
My previous analysis focused more on the nitty-gritty of trends in web advertising models, how ad blocking works, and the tensions that adblocking has created for Advertisers, Content Providers (Publishers), and Users.
This analysis focuses on wider trends in Internet access by Users that are causing large shifts in the dynamics between Advertisers, Content Providers (Publishers), and Users. In particular, three trends in Users’ Internet access are causing other ecosystem players to change the way they interact with Users: (i) Users are spending more time accessing the Internet from mobile devices than they are from non-mobile devices; (ii) Users are shifting their gateway to access to the Internet from web browsers to apps; and (iii) Users are spending more time on web platforms than they are on other, more fragmented websites.
In the first part of this analysis I describe how advertising dollars have remained relatively constant over time, even as radically new venues for ads have appeared. I then describe how it was the advent of ad networks that enabled Advertisers to cost-effectively advertise on the Internet, but that the ensuing dynamics have led to a grotesque over-proliferation of ads. I end this part with a discussion of how the ad situation for mobile Users is exacerbated by the unnecessarily poor quality of mobile web browsers.
In the second part of the analysis, I describe how trends in the way Users have been accessing the Internet have led to decreases the effectiveness of previous modes of advertising.
In the last part of the analysis I discuss how the ecosystem may continue to evolve from where it is now.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
In Part 1 of this analysis I described how advertising dollars have remained relatively constant over time, even as radically new venues for ads have appeared. I then described how it was the advent of ad networks that enabled Advertisers to cost-effectively advertise on the Internet, but that the ensuing dynamics have led to an over-proliferation of ads. I ended Part 1 with a discussion of how the ad situation for mobile Users is exacerbated by the unnecessarily poor quality of mobile web browsers.
In this second part of the analysis, I describe how trends in the way Users have been accessing the Internet have led to decreases the effectiveness of previous modes of advertising.
Three General Trends in Internet Use
The way Users have been accessing the Internet has been changing over time in three different ways: (i) by source of access, from desktop (PC) to mobile device; (ii) by mode of access, from web browsers to apps; and (iii) by destination of use: from fragmented websites to platforms.
1. Source of Access: Users Moving away from Desktop toward Mobile
In 2014 the time spent by Users accessing digital media from mobile devices surpassed the time spent by Users accessing digital media from desktop devices (see Figures 4- 5).
In Part 1 of this analysis on adblocking I described how advertising dollars have remained relatively constant over time, even as radically new venues for ads have appeared. I then described how it was the advent of ad networks that enabled Advertisers to cost-effectively advertise on the Internet, but that the ensuing dynamics have led to an over-proliferation of ads. I ended Part 1 with a discussion of how the ad situation for mobile Users is exacerbated by the unnecessarily poor quality of mobile web browsers.
In Part 2 of the analysis, I described how trends in the way Users have been accessing the Internet have led to decreases the effectiveness of previous modes of advertising.
In this last part of the analysis I discuss how the ecosystem may continue to evolve from where it is now.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
The Heart of the Matter
Figure 11 provides an illustration of the players and relationships in the Adblocking Game.
Figure 11
Source of Healthcare System Errors
Barriers to Error Reporting
Characteristics of an Ideal Error Reporting System
A 1999 study, “To Err Is Human: Building a Safer Health System” by the Institute of Medicine reports “that that at least 44,000 Americans die each year as a result of medical errors,” and “the number may be as high as 98,000…Total national costs (lost income, lost household production, disability and health care costs) of preventable adverse events (medical errors resulting in injury) are estimated to be between $17 billion and $29 billion, of which health care costs represent over one-half.”
A May 2009 study, “To Err is Human – To Delay is Deadly: Ten years later, a million lives lost, billions of dollars wasted” by the Safe Patient Project laments that since the 1999 report was issued, nothing has changed, and “we believe that preventable medical harm still accounts for more than 100,000 deaths each year – a million lives over the past decade.”
“Fake News” has become one of the big afflictions of our times. I just Googled the phrase “fake news,” and it generated 174 million hits. No one seems to know anymore whether or not any reported information is true and/or accurate. This has led people to question the truth of everything, particularly if they don’t like what’s been reported.
Trust in mass media as a whole is declining rapidly across the board. In 1976, 72% of the population had either a great del or a fair amount of trust in mass media. By 2016, that figure had declined to 32%. From Art Swift, “Americans' Trust in Mass Media Sinks to New Low” (and see Figure 1)
Americans' trust and confidence in the mass media "to report the news fully, accurately and fairly" has dropped to its lowest level in Gallup polling history, with 32 saying they have a great deal or fair amount of trust in the media. This is down eight percentage points from last year.
Gallup began asking this question in 1972, and on a yearly basis since 1997. Over the history of the entire trend, Americans' trust and confidence hit its highest point in 1976, at 72...
Figure 1
Access to true and accurate reporting of news and information is pivotal for justice and democracy to prevail. Yet, it’s become extremely difficult to ferret out the truth from news and information reports. How can we address this problem? That is, how do we encourage people to report complete and accurate information?
I don't normally write about macro issues. However, there has been a tremendous amount of debate in the media over whether the US imminently faces inflation or deflation. I've read a lot of articles on the subject and spent some time trying to puzzle out the issue for myself. And then after being asked for my opinion on the issue by several friends and family members, I decided to write this blog entry.
“Honest” Distortions of Information on the Internet
Not-So-Honest Distortions of Information on the Internet
Propagation on the Internet Promotes Distortion of Information
Governments Use the Internet to Spread Propaganda and Misinformation
Defenses Against Information Distortion
Consequences of Information Distortion
We all know there’s a lot of misinformation on the web. I started reading about this, and I soon discovered that the subject is a lot more complex that I had initially thought. There are two issues that I found particularly interesting:
1. The distinction between “honestly” inaccurate or manipulated information and purposely inaccurate or manipulated information; and
2. The dynamic surrounding how information becomes distorted as it passes from user to user on the Internet.
This analysis discusses (i) each of these two issues, (ii) defenses against being a victim of misinformation, and (iii) consequences of the increasing prevalence of misinformation on the Internet.
Persuasion technologies include methods and techniques derived from behavioral psychology and behavioral economics used to shape the choices people make. The favorable environment for using such methods, enabled by people’s increasing use of computers and smartphones, has led to the proliferation of their use by software developers.
Like any technology, persuasion technologies can be used for good or evil. However, the increasing dependence of people on digital technologies, together with the increasing prevalence of software developers’ use of persuasion technologies has created emergent behavior in society that’s downright ugly: the emergence of extremism, outrage, and divisiveness among members of society.
This analysis is closely tied to a previous analysis I performed, “Information Distortions on the Internet.”
This analysis will examine
- The nature of persuasive technologies
- The game between software developers and users that has created an environment of good, bad, and ugly
- How the environment might be changed to create more favorable social outcomes
Amazon Ecosystem Components
Amazon Segments
Amazon Sales, Income, and Margins
Amazon Methods of Competition
Anti-Trust Issues
Amazon is leaving a large pile of battered companies in its wake as it increasingly steals sales away from traditional bricks and mortar companies and decimates their market shares. Some of the better-known victims include: Barnes & Noble (books), Macy’s (clothes and home goods), Toys R Us (toys and baby products), Staples and OfficeMax (office supplies), Etsy (handmade products), and Best Buy (electronics).
In fact, there’s even an index, the Bespoke “Death By Amazon” index, that tracks the performance of 54 public companies most at risk from Amazon:
Bespoke publishes the “Death By Amazon” as a way to track performance of the companies most affected by the rise of AMZN. Companies included must be direct retailers with a limited online presence (or core business based on physical retailing locations), a member of either the Re- tail industry of the S&P 1500 Index or a member of the S&P Retail Select Index, and rely on third party brands. We view these attributes as the best expression of AMZN’s threat to traditional retail. The index is designed as both a performance benchmark and idea generation tool for our clients.
On July 17, 2017, Patti Domm reported in “Amazon's victims: These stocks have lost $70 billion so far this year” that the index is down 20% so far this year.
As Amazon’s seeks to dominate yet another market segment – the grocery business – through its plans to purchase Whole Foods, we must question once again whether or not Amazon is “too big” (however we choose to define bigness).
This analysis examines
- The various players in Amazon’s market ecosystem
- The extent to which Amazon covers its ecosystem
- How Amazon earns its money to finance its operation
- The methods Amazon uses to compete
- Other potential anti-trust issues
The Origin of Black Friday
What’s at Stake?
The Evolution of Patterns in Retail Sales
Some Issues Regarding the Black Friday Game
The Origin of Black Friday
The origin of the name Black Friday is described in “Black Friday (shopping) explained” as follows:
The day's name originated in Philadelphia, where it originally was used to describe the heavy and disruptive pedestrian and vehicle traffic which would occur on the day after Thanksgiving. Use of the term started before 1961 and began to see broader use outside Philadelphia around 1975. Later an alternative explanation began to be offered: that "Black Friday" indicates the point at which retailers begin to turn a profit, or are "in the black".
It has only been recently that Black Friday has been the busiest shopping day of the year. Previously, the busiest shopping day of the year had been the Saturday before Christmas. As Miranda Marquit describes it in “What Is Black Friday – History of the Holiday Shopping Phenomenon”
Interestingly, the day after Thanksgiving has only recently become the biggest shopping day of the year. Between 1993 and 2001, it ranked between fifth and tenth on the list of the busiest shopping days. In fact, for years, the busiest shopping day was usually the Saturday before Christmas.
But things changed in 2002. That was the year Black Friday took the lead, and it has remained the busiest shopping day of the year ever since, with the exception of 2004 when it was second.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
This section on game theory basics of war is relatively brief and non-comprehensive. The purpose of including a discussion of traditional war within an analysis of cyberwar is to provide some basics and points of reference for better understanding the challenges faced in cyberwar.
War forms a game because the actions taken by each interlinked player affect the payoffs to all other players. As such, players must act strategically, taking into account the actions they think other players might take.
Potential Actions
With traditional forms of war, players generally have three options with respect to the actions they may take: (i) They may choose not to arm themselves with weapons, (ii) they may choose to arm themselves in preparation for war against other players, or (iii) given that they have armed themselves, they may choose to attack other players.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
In Part 1: Game Theory Basics of War, I described the three potential options players may take in traditional war: don't arm, arm, or attack. I described the benefits and costs associated with arming for defense, as well as the benefits and costs associated with arming for offense or attacking. I indicated that there are ambiguities in interpretaions by players associated with the actions other players are taking: sometimes arming can increase a player’s security, while other times, arming can decrease a player’s security. I explained that there are two crucial variables that contribute to the ambiguity: (i) whether defensive weapons can be distinguished from offensive weapons, and (ii) whether defense or offense has the advantage.
Now that we have some understanding of the basics of war – the actions players are able to take, the benefits and costs associated with the different actions, and the crucial variables for determining the stability of the situation – we can move on to cyberwar. The first issue to cover is the definition of cyberwar.
Why Do We Care How Cyberwar Is Defined?
The terms cyberattack and cyberwar have been tossed around in the media, generally without the writers having provided a clear definition of terms. Why do we care about distinguishing cyberattacks from cyberwar and defining exactly what constitutes cyberwar? It is important because there are vital implications for international law and the appropriate use of policy for addressing the actions.
Part of the reason the terms have been used in such a slippery way is that cyberattacks represent a new form of attack that has not been available before now. Furthermore, attempting to frame cyberattacks in terms parallel to those of traditional, real-world attacks has proven to be problematic and not at all clear-cut.
