Saving the Future of Phone Calls – The Fight to Stop Robocalls

Saving the Future of Phone Calls – The Fight to Stop Robocalls
By Anonymous | July 5, 2019

“Hello, this is the IRS. I am calling to inform you of an urgent lawsuit! You are being sued for failing to pay taxes and we have a warrant out for your arrest. Please call this number back immediately!”

The familiar noisy background laced with thinly veiled threats is a message many are unfortunately accustomed to. Robocalls are a pervasive annoyance that has become the top consumer complaint to the Federal Trade Commission (FTC). And despite robocalls being prohibited by law, Americans were bombarded by a record breaking 4.4 billion robocalls in June 2019. That’s 145 million calls per day, 13 calls per person!

Figure 1: YouMail Robocall Index:

So, how does robocallers obtain phone number anyways? Most often, they acquire numbers from third party data providers, who in turn acquired numbers from a variety of avenues that everyday users may not be aware are collecting and selling their data. Some of these sources include:

  • Toll free (1-800) numbers that employ caller ID which can collect phone numbers
  • Entries into contests where users provided phone numbers in the process
  • Applications for credit
  • Contributions to charities where users provided phone numbers in the process

Methods of manipulating users into giving up personal information have evolved over the years as well. Robocalls can disguise their numbers to appear as a local telephone number with neighboring area codes to trick users into picking up unfamiliar calls outside of their personal contacts. The variety of robocallers disguising themselves as government agencies, municipal utility providers, or even hospital staff to scam users into providing personal information has grown to such an astonishing extent that lawmakers are now paying attention.

Figure 2: FTC Phone Scams:

In November 2018, the Federal Communications Commission (FCC) called on carriers to develop an industry-wide standard to screen and block robocalls. In particular, the FCC urged carriers to adopt the SHAKEN (Secure Handling of Asserted information using toKENs) and STIR (Secure Telephone Identity Revisited) frameworks by the end of 2019. In particular, SHAKEN/STIR frameworks employs secure digital certificates to validate that calls are from the purported source and has not been spoofed. Each telephone service provider must obtain a digital certificate from a certified authority and this enables called parties to verify the accuracy of the calling number.

Furthermore, in January 2019, Senators Edward J. Markey and John Thune introduced the Traced Act that aims to require all telephone service providers, including those over the internet such as Google Voice or Skype, to adopt similar call authentication technologies.

Together, the collective drive by private industry and regulatory efforts will make it harder for the majority of robocallers to spam consumers at the touch of a button. Like spam emails, calls with suspicious or unverified origins can be traced and blocked en masse. And though these recent tactics are certainly a step in the right direction for consumer protection, some fear that historically underserved communicated might not upgrade in time and be risk being further isolated. Rural areas that often rely on older landlines will foreseeably struggle to adopt the new technology due to outdated equipment and cost to implement. Immigrant communities who make and receive international calls to foreign countries might be subjected to higher levels of discrimination as international calls cannot yet be fully authenticated. This means their calls may be more likely to be labeled as fraud and increased targeting by robocall operatives that will exploit this gap in technology to scam an already vulnerable population.

As the world continues to evolve with newer technology, it’s important to not only think about who will benefit from these changes, but also who will be left behind. In this case, as the FCC and private industry work together to protect consumers, they should also seek to mitigate the risk of scam and spam robocalls targeting vulnerable communities. One way to accomplish this is to work with other regulatory agencies, such as the Housing and Urban Development department, to create long term and sustainable incentives within rural areas to modernize their infrastructure. Another way is for private industries who are vested in international businesses to continue working closely with regulators to develop a global SHAKEN/STIR standard that protects an increasingly globalized world. Afterall, robocalls are hardly a uniquely American phenomenon. However, taking the lead in safeguarding the next generation can be a defining American trademark.



Audit organizations, trust and their relationship with ethical automated decision making

Audit organizations, trust and their relationship with ethical automated decision making
By Jay Venkata | July 5, 2019

The world runs on trust. Worldwide billions of dollars are spent every year on developing, and maintaining trust. Any transaction, whether it be supply chain, finance or healthcare related requires trust between people, businesses and entities. As an individual consumer, you are making decisions based on trust on an almost hourly basis. This goes from trusting the safety of your meals to trusting the financial transactions done through your bank. Audit organizations and regulators, both private and public, are responsible for maintaining this trust in society. I work at one of the Big 4 global audit firms. At the core of what each of these audit companies do is giving assurance to businesses and governments. The mission statement of my company actually is ‘Solving complex problems and building trust in society’. But what does trust look like in this digital world?

[Image 1]

Trust in the Digital World

In yesteryears, audit organizations would primarily base their decisions on financial ledgers, and sources of decisions can be razored down to select executives or managers. Manual and paper based processes could only be kept track of manually. However the trend towards automating business processes, and their associated accounting and strategic decisions is causing an interesting challenge for regulators. A realm of work historically led by humans such as deciding on credit card applications can increasingly be automated. There is now a need for alternative methods to develop the same level of trust again. One solution to this issue is to focus more on independently auditing the underlying algorithms. Audit firms may need to have technical staff who can work alongside the functional experts to decode the algorithms and get to the root of any errors or biases that could affect the decisions and outcomes. Hence there is a need for accounting colleges across the world to focus on these interdisciplinary skills that will make students more ready for their careers post graduation. Another challenge is that most businesses and governments do not seem very willing to publish algorithms, the data used to train them or the inferences made from the data.

[Image 2]

Auditing the algorithms

A longer term solution that could be effective is to work alongside the government to create transparency and openness standards that are applicable to all organizations. These types of guardrails exist already in financial statements and reporting, which are managed closely by the SEC in the US. The GDPR currently has a requirement to use “appropriate mathematical or statistical procedures” to avoid or reduce risk resulting from errors or inaccuracies. The French administration also announced that algorithms developed for the government use will be made publicly available, so that society at large can verify their correct application. There needs to be a similar push worldwide for rigorous standards on automated processes and decision making to create algorithmic accountability.

[Image 3]

Blockchain improves trust in transactions through distributed ledgers

This trend towards improving and automating trust could happen naturally as we move towards technologies like Internet of Things and Blockchain, which will create end-to-end traceability for products and transactions in a cheap and ubiquitous manner. However the case for auditing algorithms is clear. Audit firms and regulators need to be one step ahead of the organizations they are auditing at all times and this applies to the current scenario where the stakes couldn’t be higher- ensuring the integrity of data flow and decision making.

Works Cited

The Role of Providers in Free Flowing data

The Role of Providers in Free Flowing data
By Hanna Rocks | July 5, 2019

In the past year, we have all experienced an inundation of emails with the subject line, “We’ve updated our privacy policies”. Recent actions by the Federal Trade Commission [1] (FTC) and the European Union (does the acronym ‘GDPR’ [2] ring any bells?) have prompted companies to make significant changes to the way they manage user information.

Despite all these changes to policies and headlines about what they hold, the majority of users continue to scroll to the bottom, check “I accept”, and move on without taking any time to consider what they are agreeing to. In fact, a study published in 2016 and updated in 2018 [3] found that 97% of users agreed to the privacy policy of a fictitious social media site—glossing over the clause requiring provision of the user’s first-born child as payment for the service.

Why are we so willing to accept any terms to gain access to an online service? The answer likely lies within the value that users receive in exchange for clicking “I accept”. A Deloitte survey [4] of over 8,500 consumers across six countries found that 79% were willing to share their personal data, *so long as there was a clear benefit to the user.*

This stance aligns with many legal and ethical opinions on privacy protections. One of the earliest regulatory frameworks on privacy harms, the Belmont Report [5], clearly states that the organization should weigh the potential for harm against the possible benefits to the individual. However, because the perceived benefit will vary from user to user, this value is difficult to define or estimate.

Instagram, for example, may define “benefit” as providing specific, personalized ad content to each user. This has also led to a heated debate about whether or not Instagram (or any other app on your phone) is “listening” to us [6]. I often wonder about this, but my worries have weakened over the years as I consume of a growing number of products found while scrolling through my feed. The value I receive from these products is worth whatever information Instagram has been collected and analyzed. I don’t know the details, so it is easy not to care.

Which brings us back to regulatory bodies like the FTC. The FTC is tasked with protecting ignorant or lazy consumers from corporations who are after unreasonable amounts of personal data. However, the question of what is deemed “reasonable” will continue to change as companies differentiate themselves by providing the ultimate personalized customer experience. More and more consumers are coming to expect tailored recommendations from the services they use—whether that is the “perfect” new pair of shoes discovered on Instagram or a carefully calculated rate from your insurance company.

As we continue down the path of highly customized goods and services, it is critical that businesses appoint individuals, or even teams, to provide oversight of what data the organization collects from its consumers and how that data is used. Doing so will benefit both the consumer and the provider by monitoring policies and comparing those policies to existing or emerging regulatory frameworks. Businesses would do well to adopt a proactive approach…

such as the “opt in” requirement under GDPR [7] that clearly addresses how they use customer data, rather than expecting consumers to read thousands of words written in the dreaded “legal-ese”. If a business is willing to invest time and resources, it *can* provide ultimate customization with ultimate protection. In the end, a business that brands itself as a leader in the responsible use of consumer data will surely attract more customers—offering both a personalized experience and peace of mind.


Search Engines and Reporting Illegal Activity

Search Engines and Reporting Illegal Activity
By Anonymous | July 5, 2019

Search engines are one of the most ubiquitous internet services and generate some of the largest databases in the world as a result. In 2012, Google handled over 1 trillion search queries [1]. However, a certain subset of such search queries point to less benign actions, and may be important clues to help identify terrorists, child abusers, human traffickers, and illegal drug traders. Should search engines be obligated to report on the potential for such illegal activity so it can be followed up on?

First we should examine how easy this would be from a technical standpoint. To do this, I went through the search logs of a major search engine to try and find a query I had input earlier.

Figure 1: Finding a user in search data: surprisingly easy.

Within a few minutes I had my nonsensical query (Column 4), the URLs I clicked (Column 6), my rough location information (Column 11), and my IP address (Column 21) which is considering personally identifying under GDPR rules [2]. If a search company were to target for other queries like “how to make a bomb” they could quickly collect the IP addresses of potential lawbreakers and cross reference with ISP companies to figure out names and home addresses. The ease of success of this experiment indicates the technical costs of implementing a filtering and reporting system to be not be a blocking issue.

There is already some basis for the idea that search engines should be obligated to report on suspected illegal activity especially regarding child abuse. In the US, all states have mandatory reporter laws that require professionals which may be seen as trusted sources for children (such as teachers, health-care workers, and child care providers) to make a report if they suspect that a child has been abused or neglected [3]. A similar law exists for companies to report child sexual abuse, which Google used in 2014 after finding explicit photos in a scan of a user’s Gmail account [4]. The law, importantly, does not require companies to be proactive and monitor or affirmatively search for illegal content which would be easy for companies to implement [5].

Figure 2: Google already searches through some user data and is mandated to report child pornography it finds.

The main drawbacks to search engines entering the space of reporting illegal activity are the concerns over a users rights and expectations to privacy. In Gonzales v. Google Inc, the U.S government subpoenaed Google and other search engine companies for queries and URLs for a study [6]. The court ruled that forcing Google to divulge query and url data would diminish user trust in the company due to the fact that users have some expectation of privacy when using the platform. It is this expectation of privacy that keeps many users from migrating away from major search engines to smaller privacy concious alternatives.

There are also issues with false positives, where users may search terms jokingly or out of curiosity and trigger automated alerts leading to unfounded accusations. This actually happened in 2013 when a counter-terrorism unit mistakenly searched a family’s home after the husband searched “pressure cooker bomb” and “backpacks” out of curiosity at work [7]. If search engines stepped into this space, law enforcement agencies may be faced with an overwhelming number of false positive cases which would waste resources and cause bad press.

Figure 3: Searching for pressure cookers and backpacks could trigger a false positive and get your house searched.

Finally, there is the argument that searches are protected under free speech. In United States v. Gilberto Valle, the US Second Circuit Court of Appeals reversed the ruling that Valle’s Google searches, which were related to fantasizing about violent crimes, themselves constituted a crime. The court reasoned that no action was taken thus no actual crime was committed, and that Valle was free to express his fanatasies [8]. This ruling was supported by a number of First Amendment and Internet law scholars and points to search queries being protected as free speech, making it more of a potential PR disaster for search engine companies to be handing it off to law enforcement or the government.

Privacy expectations and laws surrounding search engines are still a hotly debated and contested area today. The technologies to allow search engines to find and report suspected cases of illegality are easy to implement, and there is some movement in the legal sphere to cover cases like child abuse where it is clear that search engines are ethically obligated to act. On the other side, there are genuine privacy and trust concerns, false positive issues, and legal battles over the coverage of free speech that will probably keep search engine companies sidelined. Most likely, these companies will wait for the legal contests to be settled before deciding to move into any reporting of potential criminal activities unless explicitly forced to by law, so it up to all of us to decide whether the tradeoff is worth it or not.



HR Analytics – An ethical dilemma?

HR Analytics – An ethical dilemma?
By Christoph Jentzsch | June 28, 2019

In the times of “Big Data Analytics”, the “War for Talents” and “Demographic Change” the key words HR Analytics or People Analytics seem to be ubiquitous in the realm of HR departments. Many Human Resource departments ramping up their skills on analytical technologies to deploy the golden nuggets of data they have about their own workforce. But what does HR Analytics even mean?

Mick Collins, Global Vice President, Workforce Analytics & Planning Solution Strategy at SAP SuccessFactors sets the context of HR Analytics as the following:

“The role of HR – through the management of an organization’s human capital assets – is to impact four principal outcomes: (a) generating revenue, (b) minimizing expenses, (c) mitigating risks, and (d) executing strategic plans. HR analytics is a methodology for creating insights on how investments in human capital assets contribute to the success of those four outcomes. This is done by applying statistical methods to integrated HR, talent management, financial, and operational data.” (Lalwani, 2019)

Summarized, HR Analytics is a data-driven approach to HR Management.

Figure 1: Data-Driven Decision Making in HR – Source:

So, what’s the big fuzz about it? Well, the example of Marketing Analytics, which had a revolutionary impact on the field of marketing, showcases that HR analytics is changing the way how HR departments operate tomorrow. A more data-driven approach enables HR to:

  • …make better decisions using data, instead of relying on the managers gut feeling
  • …move from an operational partner to a tactical, or even strategic partner (Vulpen, 2019)
  • …attract more talent, by improving the hiring processes and the employee experience
  • …continuously improve workforce planning through informed talent development (MicroStrategy Incorporated, 2019)

However, the increased availability of new findings and information as well as the ongoing digitalization that unlocks new opportunities to understand and interpret those information, also raises new concerns. The most critical challenges are:

  • Having employees in HR functions with the right skillset to gather, manage, and report on the data
  • Confidence in data quality as well as cleansing and interpretation problems
  • Data privacy and compliance risks
  • Ethical and moral concerns about using the data

Especially, the latter 2 aspects are up for investigation and some guidance is given on how to overcome those challenges. It is important to understand in the first place that corporate organizations collect data about their employees on very detailed level. Theoretically they could reconcile findings back down the level that identifies an individual employee. However, in the considerations of legal requirements this is not always allowed and due to the implementation of GDPR regulations, organizations are now forced to look at employee data and privacy in the same way they do for customers.

Secondly, it is crucial to understand that HR Analytics uses a range of techniques based on statistics that are incredibly valuable at the population level but they can be problematic if you use them to make a decision about an individual. (Croswell, 2019)

Figure 2: HRForecast Recruiting Analytics Dashboard source:

This is being confirmed by Florian Fleischmann, CEO of HR Analytics Provider HRForecast as he states: “The real lever of HR Analytics is not taking place on an individual employee level, it is instead happing on a corporate macro level, when organizational processes, such as the hiring procedure or overarching talent programs are being improved.” (Fleischmann, 2019). Mr. Fleischmann is totally right, as managing people on an individual level is still a person-to-person relationship between employee and manger, which is nothing that requires a Big Data algorithm. Assuming the worst-case scenario: Job Cuts. If low-performers ought to be identified, simply line managers have to be interviewed – there is no need for a Big Data solution.

Analytics on an individual level do not bring added value but can even create harm as Mr. Fleischmann points out: “According to our experience the application of AI technology to predict for example, employee attrition rates on an individual basis can create more harm than benefit. It can cause a self-fulfilling prophecy, as the manager believes to know what team member is subject to leave and changes his behavior accordingly in a negative way”. (Fleischmann, 2019)

For that reason, HRForecast advocates for two paradigms in the ethical use and application for HR Analytics:

  1. Information on an employee level is only provided to the individual employee and is not shared with anyone else. “This empowers the employee to stay performant as he or she can analyze for example his or her own skill set against a benchmark of skills that are required in the future”, confirms Fleischmann.
  2. Information is being shared with management only on an aggregated level. The concept of “Derived Privacy” is applicable in this context as it allows enough insights to draw conclusions on a bigger scale but protects the individual employee. Given the legal regulations data on that level needs to be fully anonymized and groups smaller than 5 employees are excluded from any analysis. Fleischmann adds: “The implementation of GDPR did not affect HRForecast, as we applied those standards already pre-GDPR. Our company stands to a high ethical code of conduct, which is a key element if you want to be a successful player in the field of HR Analytics.”

In conclusion it can be stated that the application of Big Data Analytics or AI in a context of Human resources can create a huge leap in organizational transparency. However, his newly won information can cause major privacy risks for employees if not treated in reasonable fashion. To mitigate the risk of abusing the increased level of transparency an ethical code of conduct as provided by a third-party expert HRForecast needs to be applied in modern organizations. Thus, Big Data in HR can lead to an ethical dilemma, but it does not have to.