Artificial Intelligence Makes Harsher Judgments than Humans on Whether rules have been Broken, a new study claims.

Artificial Intelligence makes Harsher Judgments than Humans on Whether Rules have been Broken, a new study claims     By Pol Allingham via SWNS

Artificial intelligence makes harsher judgments than humans on whether rules have been broken, a new study claims. And scientists fear it might lead it to overstep the mark on punishments depending on what information it's been given.

When it is programmed based on the rules alone, with no human nuance, it is much harsher than when it's based on our responses.

The study by the Massachusetts Institute of Technology (MIT) looked at how AI would judge perceived breaches of a code.

They found the best data to program AI with is normative - where humans have stated whether or not a post breaks a certain rule. However, many models are erroneously based on descriptive data where people label the factual features of a post and AI applies the code and decides whether there’s a breach.

For the study, dog images that could violate an apartment’s rule against aggressive breeds were collected and groups were asked to give normative and descriptive responses. The descriptive team was not told about the overarching dog policy and was asked to indicate whether three factual features were presented in the image or text, such as whether the dog appears aggressive.

Their responses were used to craft judgments - if a user said the photo showed an aggressive dog, the policy was violated.  ... ' 

LPA VisiRule AutoAudit Announcement

Visirule is an interesting way to introduce process rules for integrated decisions into AI applications.

LPA announce VisiRule AutoAudit automated testing for its No-Code Low-Code visual rules tool

LPA announce a new automated testing component for VisiRule which allows VisiRule authors to test and validate their charts at a single click. VisiRule AutoAudit tests for logical consistency and completeness as well as support rule maintenance and updates.

LONDON (PRWEB) FEBRUARY 24, 2022

LPA announce a new release of VisiRule which includes VisiRule AutoAudit, an automated testing component for checking the logic of the chart.

VisiRule AutoAudit allows authors to monitor the behaviour and calculated logic contained within their charts This enables business users to validate the underlying decision logic empirically.

In its simplest mode, the module offers a single-click way to generate and execute a test suite which invokes the chart multiple times and produces an output table containing all the results. For each individual data row the table contains the conclusion reached, a success/failure indicator and, optionally, insight into internal calculations and outputs.

As test suites are generated as readable data files, they can be hand-edited by authors to target specific combinations of data values. The result is that authors can produce tables of results which show the answers the system computes for various combinations of input values in a format that can be verified and validated by external reviewers. Switches are available for authors who want to exploit VisiRule's unique backtracking mechanism to compute alternate solution sets.

In its more advanced mode the module allow authors to make changes to charts and see what effect, if any, the changes have on the resulting computations using the nominated test suite. This is aimed at projects where logic is subject to continual refinement and authors need to know that previously correct computations have not been affected by any proposed updates.  .... 

Visirule Business Risk Advisor

Have never stopped looking at simplified rule based systems to examine and  model decisions.  Some time ago we looked at some of Clive Spenser's work in this area.  Simplified and impressive.     Used similar methods in the 90s at P&G.

Storing and using complex knowledge does not have to be overly complex or too much like 'AI'.   Here it addresses risk, but can be aimed at other knowledge based applications.  Plan to test further, do take a look. Be glad to introduce you. 

Clive writes:   The BRAT initiative is based on work we have been doing for a major retail bank in the area of Testing Risk Assessment.

We simply recast it for demonstration purposes into the area of risk associated with various business activities.

The table of artifacts (Risk Areas and Risk Topics) which underpins both systems is represented using a flex frame hierarchy

The questions are standard VisiRule questions and there's a handful of statement boxes which look at the answers and determine which Risk Areas are relevant, set their initial priority levels and calculate some risk levels.

The calculated risk levels are used to calibrate the priority levels for each Risk Topic within a triggered Risk Area. Different Risk Areas are triggered by the various Business Activities.

You can play with the demo on:

https://visiruleexamples.com/visirule/tables/webflex.exe?webflex=business_risks

So the whole thing is pretty configurable and runs on our VisiRule/Flex/Prolog AWS web server using IIS/CGI  ...   

Regards,     Clive Spenser,  LPA VisiRule,  www.visirule.co.uk,    www.lpa.co.uk   

Will the FAA’s new Rules Speed Use of drones? Google Responds.

Regulating commercial delivery.

Will the FAA’s new rules speed commercialization of drones?   In RetailWire  by Tom Ryan

The Federal Aviation Administration (FAA) on Monday issued guidelines  that will soon require remote identification for any drone that has to be registered with the FAA in what could expand the use of the machines for commercial deliveries.

Drones will be required to have Remote ID, an identification technology that will enable authorities to track drones.

The FAA said in a statement, “Remote ID is a major step toward the full integration of drones into the national airspace system. Remote ID provides identification of drones in flight as well as the location of their control stations, providing crucial information to our national security agencies and law enforcement partners, and other officials charged with ensuring public safety. Airspace awareness reduces the risk of drone interference with other aircraft and people and property on the ground.”

New rules also relax restrictions for flying drones over people and at night, but add mandates that they be outfitted with anti-collision lights that can be seen for three miles. Currently, a waiver is required to fly a drone at night or over people not involved in the operation of the drone.

The rule for flying over people — which also allows for operations over moving vehicles — establishes four eligibility categories with stipulations ranging from the drone’s weight to the severity of injury they could cause in an accident. Drones also must have no “exposed rotating parts” that could cut human skin  ... ' 

Google’s Wing warns new drone laws ‘may have unintended consequences’ for privacy

 Alphabet’s drone delivery company still wants drones tracked — but differently

By Sean Hollister@StarFire2258    in TheVerge

Using Business Rules and Expertise

Via DSC, what looks to be a good podcast on this topic.  It has been a favorite approach of mine since the beginning.  Narrow machine learning methods can be very valuable, but to deliver them they have to be part of existing or proposed tasks or businesses.  Operationally embedded.   That requires real-life decision rules.  Access information to the podcast at the link below.  More on this topic to follow. 

Data Science Fails: Ignoring Business Rules & Expertise 

Nowadays, we have unprecedented access to data, plus the computing power and advanced algorithms to find correlations. We look at a cautionary case study of a cancer center that embarked on an ambitious plan to use AI to eradicate cancer. When AI is being asked to make decisions with significant consequences, such as life and death healthcare recommendations, it needs to be trustworthy. But if you don't follow best practices, if you don't include the knowledge of subject matter experts, and if you don't enforce business rules, your AI project will not be successful.

In this latest Data Science Central podcast, learn four AI governance practices that can help you achieve AI success.

Speaker: Colin Priest, VP of AI Strategy - DataRobot
Hosted by: Sean Welch, Host and Producer - Data Science Central .... 

When the Brain Switches Rules

An architectural approach for AI?    A concierge like approach?  Explicit rules, or just weights changed for perception, interaction?  Architectural implications.  An Opportunity for Context Clustering and Classification?

How the brain switches between different sets of rules
When you slow down after exiting the highway, or hush your voice in the library, you’re using this brain mechanism.   By Anne Trafton | MIT News Office 

Cognitive flexibility — the brain’s ability to switch between different rules or action plans depending on the context — is key to many of our everyday activities. For example, imagine you’re driving on a highway at 65 miles per hour. When you exit onto a local street, you realize that the situation has changed and you need to slow down. ... "

Machine Learning Extrapolates

Powerful idea,  requires some underlying 'physics' to be in place.   Could that base information be the business process, or some other grounding rules?  As I see it this also increases interpretability because of the rules involved, and the ability to derive them.

Machine Learning Extrapolates
An illustration of a robot learning about this body and the environment. First Machine Learning Method Capable of Accurate Extrapolation
IST Austria

Researchers at the Institute of Science and Technology Austria and the Max Planck Institute (MPI) for Intelligent Systems in Germany have developed a machine learning method that uses observations made under safe conditions to accurately extrapolate all possible conditions shaped by the same physical dynamics. MPI's Georg Martius says the method digests data from which it extracts the equations describing the underlying physics. The technique also yields more intuitive and understandable equations, and it ensures interpretability and optimization for physical situations because it is founded on a different type of framework than other machine-learning techniques. Martius envisions this research being applied to a future scenario in which "[a] robot would experiment with different motions, then be able to use machine learning to uncover the equations that govern its body and movement, allowing it to avoid dangerous actions or situations."  ... 

Tutorial on Association Rules

Good piece in KDNuggets,  the approach is useful because it is transparent and thus easily visualized. Here is a further technical definition,  from the approach of set mining and rule generation.  Note this applies in many domains.  We used this to generate initial sample expert rule sets.  The method can be extending to the idea of a knowledge graph.  Below the tutorial introduction:

Association Rules and the Apriori Algorithm: A Tutorial
A great and clearly-presented tutorial on the concepts of association rules and the Apriori algorithm, and their roles in market basket analysis.

The (an Example) Problem

When we go grocery shopping, we often have a standard list of things to buy. Each shopper has a distinctive list, depending on one’s needs and preferences. A housewife might buy healthy ingredients for a family dinner, while a bachelor might buy beer and chips. Understanding these buying patterns can help to increase sales in several ways. If there is a pair of items, X and Y, that are frequently bought together:

Both X and Y can be placed on the same shelf, so that buyers of one item would be prompted to buy the other.

Promotional discounts could be applied to just one out of the two items.
Advertisements on X could be targeted at buyers who purchase Y.
X and Y could be combined into a new product, such as having Y in flavors of X.
While we may know that certain items are frequently bought together, the question is, how do we uncover these associations?

Besides increasing sales profits, association rules can also be used in other fields. In medical diagnosis for instance, understanding which symptoms tend to co-morbid can help to improve patient care and medicine prescription.

Definition

Association rules analysis is a technique to uncover how items are associated to each other. There are three common ways to measure association. .... "

Developers Eye View of Smart Contracts

Its all about business rules.  So its about rule based process.  But why do it this way in particular rather than using rule bases and encrypted ledgers ?  Case is made here.  (Much more in full piece at the link)

Make your blockchain smart contracts smarter with business rules
By Stephane Mery and Daniel Selman  IBM

Blockchain already has a profound impact on multi-party business processes. Organizations that use blockchain count on trusted automatic transactions. It provides a framework of trust that you can use to securely automate processes that, until now, were often manual.

Traditionally, in business transactions, when two parties exchange value, they need to share a representation of the exchanged value and of the terms and conditions for the transaction. If they can't fully trust each other, each party maintains its own record of the exchange – a transaction ledger. They also keep their own copies of the rules and processes that govern the contract to exchange value.

Duplicating these records can lead to errors – and fraud. On top of this, the transaction processes are also duplicated, and performed manually and inefficiently. Disputes over discrepancies between the copies of the ledgers and contracts might need to be resolved in court, leading to significant costs, and ultimately delays to the transaction.

Blockchain uses cryptography along with distributed computing and storage technologies to solve the problems inherent in the traditional processes by providing trading parties with a means to share a trusted representation of their transactions and their assets.  ....  " 

Explaining Smart Contracts

Have worked with companies that set simple alarms to warn them of renewal dates and expiration of contracts.  This takes it much further.  Good simplified view.

What Are Smart Contracts? They Could Help Optimize Your Business Processes   Should your business consider implementing smart contracts? Let's explore how complicated or automated the process involves.     By Drew Hendricks  in Inc.

Advances in technology continue to impact all areas of our society, including business. These advances will help solve everyday problems and help increase our efficiency. As Blockchain, or distributed ledger technology, becomes more popular, a new workflow automation technology was created - smart contracts.

Value proposition of Blockchain

In order to understand smart contracts, we first have to understand the value of Blockchain. It is infamous enough in itself for its inherent notoriety in the learning curve. Smart contracts can then make or break whatever one has learned in Blockchain.

The beauty, though, with this is that business transactions are now more transparent. Each involved user will then see the respective operations of each transaction, so that the latter becomes much more optimized.  .... "

Articles about Decision Trees

Good list from DSC of articles about decision trees, provided by Vincent Granville.    We found much value in the enterprise of these methods because their output was explainable to decision makers.   In addition we were able to use these results directly plugged into rule based expert systems to implement AI.  I still believe there is value in such rule bases to implement knowledge in simple logic directly.  Such systems still exist, for example, Visirule, recently updated, which we examined as early as 2009.

Pew Internet Research Looks at Algorithms

I like their broad definition of algorithms.  Sometimes the implication is falsely given that algorithms are some magical and very complex thing.    But they are simply the way that some processes can be driven by rules.  How these are constructed by analytics can be complex.  Or not, and its better if they are simple and thus transparent.  Its the operational aspects of how this is done and managed that is important.

In PewInternet: 
Algorithms are instructions for solving a problem or completing a task. Recipes are algorithms, as are math equations. Computer code is algorithmic. The internet runs on algorithms and all online searching is accomplished through them. Email knows where to go thanks to algorithms. Smartphone apps are nothing but algorithms. Computer and video games are algorithmic storytelling. Online dating and book-recommendation and travel websites would not function without algorithms. GPS mapping systems get people from point A to point B via algorithms. Artificial intelligence (AI) is naught but algorithms. 

The material people see on social media is brought to them by algorithms. In fact, everything people see and do on the web is a product of algorithms. Every time someone sorts a column in a spreadsheet, algorithms are at play, and most financial transactions today are accomplished by algorithms. Algorithms help gadgets respond to voice commands, recognize faces, sort photos and build and drive cars. Hacking, cyberattacks and cryptographic code-breaking exploit algorithms. Self-learning and self-programming algorithms are now emerging, so it is possible that in the future algorithms will write many if not most algorithms.

Algorithms are often elegant and incredibly useful tools used to accomplish tasks. They are mostly invisible aids, augmenting human lives in increasingly incredible ways. However, sometimes the application of algorithms created with good intentions leads to unintended consequences. ... " 

Rulex: Modeling for Rule Based Decision Making

Had spent some time looking at rule based approaches to doing predictive decisions.  Brought to my attention:  Rulex:

 " ... Understand, Forecast, Decide.
New generation advanced analytics tools for proactive decision makers. ... 

Big Data, Predictive and Prescriptive Analytics, Modelling, Forecasting and Data Challenges Beyond all the keywords, you are fighting Complexity.  Rulex gives you the tools to dominate it. ... " 

Chatham House Rules

This was brought to mind during planning for a meeting, I researched the background of the 'Chatham house rules', which we used at times when working with external experts:  From the Wikipedia:

" ... The Chatham House Rule or rules is a system for holding debates and discussion panels on controversial issues, named after the headquarters of the Royal Institute of International Affairs (situated in St James's Square, London), also known as Chatham House, where the rule originated in June 1927.

At a meeting held under the Chatham House Rule, anyone who comes to the meeting is free to use information from the discussion, but is not allowed to reveal who made any comment. It is designed to increase openness of discussion.  ... " 

Don't Bury Business Rules Management

Back in 2012 I wrote a post on Business Rules Management.   This is related to work we had done with expert systems in the enterprise.   Based on conversations I have now had, this rebranding of the former Ilog JRules capability has buried its existence.   It would appear that the capability would be particularly important to connect to Big Data Analytics to real workflow decision streams.    Are there plans to integrate Watson and rule streams?  Can I ask someone at IBM to contact me on this?  Have real applications.

Rules and Decision Management

The large enterprise can think about how to systematize their business processes and the rules that they use to make decisions.  This has often been difficult for the midsize to smaller business.  The systems have not existed to help these businesses think through how their business should work well to grow and be profitable. These businesses have their own internal expertise, but do not typically have the internal resources for other specialized knowledge.

In the large enterprise we used methods called expert systems.  We interviewed dozens of experts and then placed their expertise in sets of rules.  These were then combined with analytical methods to calculate and adjust the results of particular choices to optimize results based on the rules .  This created a simulation of a specific set of  business decisions.  When we did not have internal experts available for a set of decision rules, we went outside to interview experts that had additional domain knowledge we could readily insert into the process.

A recent discussion with a Mid Size business led me to take another look at this area.  The business had some quantitative methods that calculated results, but did not have a means to implement their business rules. I needed a better way to generate these rules from flowcharts of their processes.

I had previously looked at the Ilog JRules capability for delivering decision rules.  Now re-branded as Operational Decision Management.   Also to be seen on the  IBM Decision Management page on Facebook.  Check this out as a method to implement rules within business processes.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines  of a smarter planet. More on that here: http://goo.gl/S6P7m 

Decision Management Systems: Rules and Analytics

Business Rules and Predictive analytics from SAP.   Link to an excerpt from a forthcoming book that I am looking at now.  This topic has been much in my mind of late.  We know that business process is delivered by rules,  precise or imprecise.  But how can predictive analytics be driven by these very same rules?    A cause for simulation via agents?     Don't know yet if that is covered, but I will explore.

Hanlon's Razor

Some reading reminded me of the principle of Hanlon's razor:  Never attribute to malice that which is adequately explained by stupidity.  ... Though I recall this was sometimes dangerous to invoke within some organizations.