chapter 15: data and competitive advantage: databases, analytics, AI, and machine learning

loan approval

AI is increasingly used in the _____ ____ process, and some customers may face exclusion without knowing why

artificial intelligence

Computer software that can mimic or improve upon functions that would otherwise require human intelligence.

not enough data

A firm might want to get into machine learning, but may lack underlying databases to begin this effort. It might, for example, be impossible to use machine learning to develop a system to predict failure when there are very few cases of failure that occur, and hence not enough examples to learn from. This also applies to the inability to predict rare "black swan" events since, by definition, they are either exceedingly rare or have never previously occurred.

neural networks

A statistical techniques used in AI, and particularly in machine learning. Neural networks hunt down and expose patterns, building multilayered relationships that humans can't detect on their own. identify patterns by testing multilayered relationships that humans can't detect on their own

Provide a means for remediation

A study led by technology and audit firms found that only 43 percent of organizations have clear procedures for overriding AI results that are suspicious or questionable. Like steps identified in our Social Media chapter regarding SMART (the social media awareness and response team), those associated with AI and broader systems use should have mechanisms not only for prevention and monitoring, but also for clear action when issues arise. All employees should know how to "pull the alarm" to raise concern, and there should be an existing plan of action that firms can take to mitigate any damage caused by current systems. If redress needs to occur, enforcement mechanisms should ensure that they operate entirely independently, as studies have repeatedly shown that executives with friendships or working relationships cannot be counted on to act reliably. In the event that a whistle-blower identifies egregious and malicious system use, or deliberate negligence, then those reporting should have guarantees that they will not face retaliation.

machine learning

A type of artificial intelligence that leverages massive amounts of data so that computers can improve the accuracy of actions and predictions on their own without additional programming. a type of AI often broadly defined as software with the ability to learn or improve without being explicitly programmed. Many of the data mining techniques described in the prior section use ________ _______

deep learning

A type of machine learning that uses multiple layers of interconnections among data to identify patterns and improve predicted results. Deep learning most often uses a set of techniques known as neural networks and is popularly applied in tasks like speech recognition, image recognition, and computer vision.

ApplePay

AI fights fraud by improving analysis with each transaction

Maps

AI helps plot the best route by analyzing all sorts of traffic input

human resources

AI is increasingly embedding itself into the soft-skills discipline of ______ ______ Software from the SaaS vendor Workday provides software to improve employee retention by uncovering patterns of those most likely to leave. The firm's software examines some 60 factors, including salary, time between holidays taken, and turnover of the employee's manager

expert systems

AI systems hat leverage rules or examples to perform a task in a way that mimics applied human expertise used in tasks ranging from medical diagnoses to product configuration. They may be programmed with explicit rules (think a big "if this, then do that" decision tree), or rules may be automatically built by analyzing specific cases against outcomes (e.g., make less product if the weather is below 40 degrees and rainy, since there will be less foot traffic).

Create and enforce technology audit trails

An audit trail exposes how and when information systems are used so that the way a firm arrived at a particular outcome can be identified. Audit trails can also ensure triggers to identify problems and prevent common issues that may include illegal data access; and unsafe data exposure to existing staff, contractors, or external parties. As legal frameworks develop worldwide, audit trails will play a critical role in lawsuits, arbitration, or other judicial proceedings. Firms should expect to have to make changes to auditing mechanisms as legal requirements dictate parameters around data collection and system use. Major accounting firms also have extensive technology audit practices that can provide valuable (and sometimes legally required) audit skills.

Siri

Data collected and constantly analyzed by _____ helps the voice assistant continually improve with better understanding of voices and accents worldwide, develop a greater understanding of context, and parse how devices are used so it can better service requests

Implement strong tech and procedural training programs

Ethical system use is a concern throughout the organization, from the most senior C-level and board members to front-line workers and contractors that interact with data collection, decision-making, and operational systems. A broad training program would raise legal, ethical, and technical issues so that everyone at all levels in the organization become partners in improvement, as well as strengthening the eyes and ears of risk mitigation.

bad algorithmic insight

Example of _____ _______ _______: An Amazon hiring model had downgraded candidates from all-female colleges since no one from its male-heavy engineering staff went there

Core ML

Expect even more since third parties have access to many of these tools, too. Apple's custom processors and the firm's _____ ___ software developer framework allow coders to tap into Apple and third-party machine learning algorithms so that apps can take advantage of image recognition, natural language processing, computer vision, and more. Tools like these create standards and prevent developers from having to create things from scratch, enabling even small-time programmers to cheaply, easily, and quickly incorporate AI in their products.

genetic analysis

Fast/cheap computing has enabled modern _____ ______

Hire ethicists

Few technologists (or managers in general) have had significant training in technology ethics. Microsoft and Salesforce are among firms that have brought professional ethicists on board to work side-by-side with technologists and decision-makers, and to vet existing products and data use. The WSJ reports that these ethicists have vetted algorithms for gender and racial bias, worked to surface the unintended consequences of planned and existing systems, and raised risks that could present legal and PR risks. Other tasks of ethicists would include an annual (or more regular) report outlining new policies, concerning issues that have occurred, and steps taken. Ethicists can also ensure that an organization has policies in effect for audit, issue identification, system shutdown, and remediation.

reCAPTCHA

Google's widely used method that asks users to prove their superior-to-robot chops by classifying images, such as hard-to-read letters, house numbers, and to identify squares containing stop lights and traffic signs

Create a systems review board

It's important that many voices are involved in identifying, heading off, or responding to issues that may arise. The board should have the perspective of deeply-knowledgeable technologists, senior executives, legal, and public relations representatives. Organizations would be wise to regularly involve government and consumer advocacy organizations in their efforts to ensure the broadest-possible risk assessment and updated issues and technical awareness is being considered. Members should regularly attend conferences and participate in industry groups concerned with responsible technology use, especially those that develop and share evolving best practices. Without broad perspectives in a room, many risks may go unnoticed. Consider that Lyft's IPO filings reported a risk normally associated with medical providers under HIPAA provisions, such as when medical providers use Lyft's Concierge product to schedule rides for patients

true

T/F: in the United States, just about anything done on organizational networks or using a firm's computer hardware can be monitored. While examining worker communications can help ensure employees don't break the law or commit crimes against the firm, and can offer help on how to do one's job better, the acceleration of these practices will undoubtedly raise additional privacy issues and have the potential to alienate workers, especially in a tight labor market.

Develop a code of technology ethics

Many organizations have 'core values' shared throughout the organization. Firms should develop and continue to refine systems development ethics in an effort to keep risks and responsibility top-of-mind among technologists and other decision-makers that lay out how various issues will be handled. Firms should share the code and extend behavior expectations to partners throughout its value chain. Technologists can also ensure that firms continue to deploy state-of-the-art tools to help improve the ethical robustness of systems development. Examples of technology that can help enforce better practices include Google's TensorFlow Privacy, which provides mathematical guarantees that models don't "remember" details about a specific user, and the third-party TF Encrypted library that adds additional privacy-preserving technology to machine learning efforts that use Google's popular model-building TensorFlow product.

biases

Since AI systems "learn" based on data, then any ______ in data can become part of the model.

optical character recognition (OCR)

Software that can scan images and identify text within them algorithms that turn images into text

true

T/F: Data quality, inconsistent data, or the inability to integrate data sources into a single dataset capable of input into machine learning systems can all stifle efforts

true

T/F: Facial recognition systems built using data with mostly Caucasian faces have been shown to be weaker in identifying people of color

true

T/F: Industry leaders including Amazon, Apple, Facebook, Google, IBM, and Microsoft, working with additional participants, such as the human rights organization Amnesty International, have come together to co-create a set of best practices and guidelines in what is called the "Partnership for Artificial Intelligence to Benefit People and Society"

true

T/F: Like systems and technologies are as varied as religion, capitalism, and even fire, machine learning can have positive and negative uses and well as intended and unintended consequences

true

T/F: Some types of machine learning may be legally prohibited because of the data used or the inability to identify how a model works and whether or not it might be discriminatory. For example, while gender and religion could be used to predict some risks, they are unacceptable to regulators in some applications and jurisdictions. Redlining laws in the lending industry prevent geography from being used in calculating credit worthiness, since geography is often tightly correlated with race. In other industries, regulators won't accept the "black box" solutions offered by neural networks. And some areas such as the EU may have higher privacy protection that prohibits the gathering or use of certain data or techniques.

true

T/F: Technical staff may require training in developing and maintaining such systems, and such skills are rare. In situations where AI makes a recommendation, but a human makes the final call, managers using such systems may need coaching on when to accept and when to question results (see the Tesco "milk loaf" example in the prior section). Machine learning may mean more human learning at all levels of the organization.

true

T/F: While AI is not a single technology—terms and categorizations may overlap or have debated definitions—various forms of AI can show up as part of analytics products, CRM tools, transaction processing systems, and other information systems

true

T/F: as we think of how data relates to competitive advantage, firms that gain an early lead and benefit from scale may be in a position to collect more data than competitors, fueling a virtuous cycle where early winners generate more data, have stronger predictive capabilities, and can have an edge in entering new markets, offering new services, attracting customers, and cutting prices. Good for the winners and possibly good for consumers in the short run, but this may also fuel the kind of winner-take-all / winner-take-most dominance we see when network effects are present, something that might stifle innovation if it discourages competition and feeds near-monopolies. Indeed, many have referred to data as "the new oil," in that it is has the ability to create cash-gushing opportunities.

true

T/F: in the age of Big Data, employment, insurance, and loan applications are increasingly being evaluated by data mining models that are not as overt but may be even more pernicious than color-coded maps, because they are not limited by geographic boundaries, and because their inner workings are often hidden

completely automated public Turing test to tell computers and humans apart (CAPTCHAs)

The Turing Test is, rather redundantly, an idea (rather than an official test) that one can create a test to tell computers apart from humans meant to keep out automated software that may create accounts used in spamming or other nefarious activity

misuse

The negative unintended consequences of data ______ might also lead to regulation that limits techniques currently used. Some believe this helps give China an edge in some systems, since the government keeps a vast database of faces that can help train facial-recognition algorithms, and privacy is less of a concern than in the West. Jaywalkers in Shanghai can already be fined (or shamed) from facial recognition that identifies scofflaw citizens. In another example, The Chinese financial firm Ping An uses app-based video interviews to spot shifty behavior worthy of further screening. Prospective borrowers answer a series of questions related to income and ability to replay a loan, while machine learning systems monitor and identify some fifty distinct facial expressions related to truthfulness. The camera and the cloud are becoming a sort of real-time lie detector.

computer vision

Uber uses Microsoft-provided ____ _____ to scan driver faces and confirm their identity when they are starting a shift. The congressional television network C-SPAN uses Amazon's image recognition tools to identify on-screen lawmakers so they can quickly place a name below their image.

AI

___ is behind extending device battery life, auto-switching between cellular and Wi-Fi networks, choosing news stories, apps, music, and video content you might enjoy

multilayered interconnections

______ _____ among data referred to as mimicking the neurons of the brain If a set of interrelationships is strong, they go into the pattern-matching scheme. If a better set of relationships is found, old ones are tweaked or discarded. Neural networks are often referred to as a "black box," meaning that the weights and relationships of data that identify patterns approximate a mathematical function, but are difficult to break out as you would in a traditional mathematical formula.

tools

an explosion of ____ is fueling the current spread of AI, including a new generation of hardware chips that fuel AI through designs tailored to find patterns faster, cloud resources that any developer with a credit card can tap into, open source algorithms that can be applied to creating custom insights, software development kits that create standards for building AI into apps and other products, and data-capture tools that include sensors, cameras, and microphones

genetic algorithms

model-building techniques where computers examine many potential solutions to a problem, iteratively modifying (mutating) various mathematical models, and comparing the mutated models to search for a best alternative function. Many computer scientists would say that neural networks approximate functions, while ______ ______ refine functions to optimize solutions. For most managers it's useful just to know the term as a type of automated model development that's another arrow in the AI quiver. ______ ______ have been used for everything from building financial trading models to handling complex airport scheduling to designing parts for the international space station.

Toronto Declaration

rafted and originally signed by organizations as diverse as Amnesty International, Access Now, Human Rights Watch, and the Wikimedia Foundation, called on algorithms to respect human rights. Recommendations include the 'right to remedy' algorithmic discrimination or similar code-caused injustice, as well as calls for developers to work to identify risks in advance, ensure transparency, develop and enforce oversight mechanisms, and hold violators accountable

change management

seeks to identify how workflows and processes are to be altered, and how to manage the worker and organizational transition from one system to another. This can be key because many users of corporate AI will see their jobs significantly altered. They might have to do more, take on more responsibility, or remove instinct from some decisions and rely on recommendations made by a machine

naked algorithms

starting point algorithms, and many are in the public domain or accessible from cloud provider services (e.g., Google TensorFlow) or through vendor APIs and inside software development kits (e.g., Apple Core ML). AI stars with ______ ______ that need to be trained

hire ethicists, develop a code of technology ethics, create a systems review board, create and enforce technology and audit trails, implement strong tech and procedural training programs, provide a means for remediation

steps that organizations should take to help broaden the scope of their awareness of the implications of AI and machine learning, steps that can help craft better, more secure, and more socially-beneficial systems, reduce public or organizational harm, and provide mechanisms for redress. While crafted to focus on AI and machine learning, the steps are broadly applicable in information systems development, and have wider implications in product and system design, as well. These steps include (6)

black box

the "____ ___" nature of machine learning, with multi-layered statistical weightings, is especially difficult to break apart in a clear demonstration of how, exactly, systems make their decisions Such systems heighten the possibility of unintended consequences, including software that inadvertently crosses ethical boundaries

supervised learning

where algorithms are trained by providing explicit examples of results sought, like defective vs. error-free, or stock price

unsupervised learning

where data are not explicitly labeled and don't have a predetermined result. Clustering customers into previously unknown groupings machine be one example

semi supervised learning

where data used to build models that determine an end result may contain data that has outputs explicitly labeled as well as unlabeled, e.g., "hey software, take a look at my categorizations and see if they are valid or you can come up with better or missing ones"