Categoría: Recursos Humanos

Artificial Intelligence, Privacy and Google: An explosive mix

A few days ago, I knew about a big company using AI in the recruiting processes. Not a big deal since it has become a common practice and if something can be criticized, is the fact that AI commits the same error that human recruiters: The false-negative danger; a danger that goes far beyond recruiting.

The system can have more and more filters, learning from them but…what about the candidates that were eliminated despite they could have been successful? Usually, we will never know about them and, hence, we cannot learn from our errors rejecting good candidates. We know of cases like Clark Gable or Harrison Ford that were rejected by Hollywood but, usually, following the rejected candidates is not feasible and, then, the system -and the human recruiter- learns to improve the filters but it’s not possible learning from the wrong rejections.

That’s a luxury that companies can afford while it affects to jobs where the supply of candidates and the demand for jobs is clearly favorable. However, this error is much more serious if the same practice applies to highly demanded profiles. Eliminating a good candidate is, in this case, much more expensive but both, AI system and human recruiters, don’t have the opportunity to learn from this error type.

Only companies like Google, Amazon or Facebook with an impressive amount of information about many of us could afford to learn from the failures of the system. It’s true that, as a common practice, many recruiters “google” the names of the candidates to get more information, but these companies keep much more information about us than the offered when someone searches for us in Google.

Then, since these companies have a feature that cannot be reached by other companies, including big corporations, we could expect them to be hired in the next future to perform recruiting, evaluate insurance or credit proposals, evaluation about potential business partners and many others.

These companies having so much information about us can share Artificial Intelligence practices with their potential clients but, at the same time, they keep a treasure of information that their potential clients cannot have.

Of course, they have this information because we voluntarily give it in exchange for some advantages in our daily life. At the end of the day, if we are not involved in illegitimate or dangerous activities and we don’t have the intention of doing it, is it so important having a Google, Amazon, Facebook or whoever knowing what we do and even listening to us through their “personal assistants”? Perhaps it is:

The list of companies sharing this feature -almost unlimited access to personal information- is very short. Then, any outcome from them could affect us in many activities, since any company trying to get an advantage from these data is not going to find many potential suppliers.

Now, suppose a dark algorithm that nobody knows exactly how it works deciding that you are not a good option to get a job, insurance, a credit…whatever. Since the list of suppliers of information is very short, you will be rejected once and again, even though nobody will be able to give you a clear explanation of the reasons for the rejection. The algorithm could have chosen an irrelevant action that happens to keep a high correlation with a potential problem and, hence, you would be rejected.

Should this danger be disregarded? Companies like Amazon had their own problems with their recruiting systems when, unintendedly, they introduced racial and genre biases. There is not a valid reason to suppose that this cannot happen again with much more data and affecting many more activities.

Let me share a recent personal experience related to this error type: Recently, I was blacklisted by a supplier of information security. The apparent reason was having a page, opening automatically every time I opened Chrome, without further action. That generated repeated accesses; it was read by the website as an attempt to spy and they blacklisted me. The problem was that the supplier of information security had many clients: Banks, transportation companies…and even my own ISP. All of them denied my access to their websites based on the wrong information.

This is, of course, a minor sample of what can happen if Artificial Intelligence is applied over a vast amount of data by the few companies that have access to them and, because of reasons that nobody could explain, we must confront rejection in many activities; a rejection that would be at the same time universal and unexplained.

Perhaps the future was not defined in «1984» by Orwell but in “The process” by Kafka.

A contracorriente: ¿Libertad de información o libertad de difamación?

Creo que en ciertos momentos es necesario dejar clara la posición personal para evitar confusiones, de modo que allá va:

No me gusta la forma en que ha llegado al poder en España el líder del PSOE, Pedro Sánchez, no me gusta su actuación en los principales temas de España, no me gustan sus socios, no me gusta que remolonee en la convocatoria de elecciones y la ocultación de su tesis me parece un asunto sospechoso del que el tiempo dirá, a corto plazo, si hay algo real o es una tormenta en un vaso de agua. Está claro ¿verdad?

Sin embargo, me parece impresentable que el gran asunto actual no sea nada de eso sino que haya osado exigirles la rectificación a algunos medios de comunicación y cómo esa exigencia atenta supuestamente contra la libertad de información. En esta trampa han caído interesadamente periodistas y políticos e intentan que los demás caigamos también. Pues no:

La libertad de información no es un derecho del periodista a decir lo que le parezca sino un derecho del ciudadano a recibir información cierta y desde la perspectiva que a ese ciudadano le apetezca.

Si el periodista difama, está tan sujeto a la ley como cualquier otro y no puede invocar la libertad de información como si fuera una patente de corso.

Si alguien, en este caso un presidente de un Gobierno y con independencia de la opinión que se tenga de él, cree que ha sido difamado por un medio de comunicación está en su perfecto derecho de exigir una rectificación.

¿Quiere llevar el asunto a los tribunales? Adelante; es su derecho aunque sea una jugada arriesgada porque, si pierde, no tendrá manera humana de amarrarse a un sillón al que ha llegado de una forma tan irregular.

Desde luego, quien no puede ni debe tratar de impedírselo son los medios de comunicación, alegando libertad de información que, al parecer, consideran sinónimo de libertad para decir lo que les de la gana.

Insisto: No defiendo al personaje sino su pleno derecho a acudir a instancias judiciales si cree que ha sido difamado. Si lo ha sido o no, ya lo veremos pero no cabe rasgarse las vestiduras por un atentado a la libertad de información ante el ejercicio de tal derecho.

THE HARD LIFE OF AVIATION REGULATORS (especially, regarding Human Factors)

There is a very extended mistake among Aviation professionals: The idea that regulations set a minimum level. Hence, accepting a plane, a procedure or an organization means barely being at the minimum acceptable level.

The facts are very different: A single plane able to pass, beyond any kind of reasonable doubt, all the requirements without further questions would not be an “acceptable” plane. It would be an almost perfect product.

Then, where is the trick and why things are not so easy as they seem to be?

Basically, because rules are not so clear as pretended, giving in some cases wide room for interpretation and because, in their crafting, they are mirroring the systems they speak about and, hence, integration is lost in the way.

The acceptance of a new plane is a very long and complex process till the point that some manufacturers give up. For instance, the Chinese COMAC built a first plane certified by Chinese authorities to fly only in China or the French Dassault decided to stop everything jumping directly to the second generation of a plane. It be judged a failure, but it is always better than dragging design problems until they prove that they should have been managed. We cannot avoid to remind cases like the cargo door of DC10 and the consequences of a problem already known during the design phase.

The process is so long and expensive that some manufacturers keep attached to very old models with incremental improvements. Boeing 737, that started to fly in 1968, is a good example. Its brother B777, flying since 1995, keeps a very old Intel-80486 processor inside but changing it would be a major change, despite Intel stopped its production in 1997.

The process is not linear, and many different tests and negotiations are required in the way. Statements of similarity with other planes are frequent and the use of standards from Engineering or Military fields is common place when something is not fully clear in the main regulation.

Of course, some of the guidelines can contradict others since they are addressed to different uses. For instance, a good military regulation very used in Human Factors (MIL-STD-1472) includes a statement about required training, indicating that it should be as short as possible to keep full operating state. That can be justified if we think in environments where lack of resources -including knowledge- or even physical destruction could happen. It should be harder to justify as a rule in passenger’s transportation.

Another standard can include a statement about the worst possible scenario for a specific parameter, but the parameter can be more elusive than that. The idea itself of worst possible scenario could be nonsense and, if the manufacturer accepts this and the regulator buys it, a plane could by flying legally but with serious design flaws.

Regulations about Human Factors were simply absent a few years ago and HF mentions were added to the technical blocks. That was partially changed when a new rule for planes design appeared addressing precisely Human Factors as a block on its own. However, the first attempts were not much further than collecting all the scattered HF mentions in a single place.

Since then, it has been partially corrected in the Acceptable Means of Compliance, but the technical approach still prevails. Very often, manufacturers assemble HF teams with technical specialists in specific systems instead of trying a global and transversal approach.

The regulators take their own cautions and repeat mantras like avoiding fatigue levels beyond acceptability or planes that could not require special alertness or special skill levels to manage a situation.

These conditions are, of course, good but they should not be enough. Compliance with a general condition like this one, in EASA CS25  “Each pilot compartment and its equipment must allow the minimum flight crew (established under CS 25.1523) to perform their duties without unreasonable concentration or fatigue” is quite difficult to demonstrate. If there is not a visible mistake in the design, trying to meet this condition is more a matter of imagining potential situations than a matter of analysis and, as it should be expected, the whole process is driven by analysis, not by imagination.

Very often, designs and the rules governing them try to prevent the accident that happened yesterday, but a strictly analytic approach makes hard to anticipate the next one. Who could anticipate the importance of controls feedback (present in every single old plane) until a related accident happened? Who could anticipate before AA191 that, perhaps, removing the mechanical blockage of flaps/slats could not be so sound idea? Who could think that different presentations of artificial horizon could drive to an accident? What about different automation policies and pilots disregarding a fact that could be disregarded in other planes but not in that one?…

Now, it is still in the news the fact that a Boeing factory had been attacked by the WannyCry virus and the big question was if it had affected the systems of the B777s that were manufactured there. B787 is said to have 6,5 million of code lines. Even though B777 is far below that number, checking it should not be easy and it should be still harder if computers calculating parameters for the manufacturing must be also checked.

That complexity in the product drives not only to invisible faults but to unexpected interactions between theoretically independent events. In some cases, the dependence is clear. Everyone is conscious that an engine stopped can mean hydraulic, electric, pressure and oxygen problems and manufacturers try to design systems pointing to the root problem instead of pointing to every single failure. That’s fine but…what if the interaction is unexpected? What if a secondary problem -like oxygen scarcity, for instance- is more important than the root problem that drove to this? How are we going to define the right training level for operators where there is not a single person who understands the full design?

In the technical parts, the complexity is already a problem. When we add the human element, its features and what kind of things are demanded from operators, the answer is everything but easy. Claiming “lack of training” every time that something serious happens and adding a patch to the present training is not enough.

A full approach more integrated and less shy to speak about using imagination in the whole process is advisable long ago but now it is a must. Operators do not manage systems. They manage situations and, at doing so, they can use several systems at the same time. Even if there is not an unexpected technical interaction among them, there is a place where this interaction happens: The operator who is working with all of them and the concept of consistency is not enough to deal with it.

 

El efecto Twitter

Mucha gente considera Twitter como un sitio poco serio y, por tanto, decide no tener una cuenta en Twitter. Grave error:

Muchos individuos y publicaciones muy conocidos tienen sus cuentas y publican regularmente contenidos. Es cierto que 140 caracteres no dan para mucho pero la cosa se pone más interesante si se considera que, dentro de esos 140 caracteres, puede haber vínculos a artículos recién publicados por ellos mismos.

Seguir a mucha gente es enloquecedor porque, a menos que se viva con la nariz pegada a la pantalla, se perderá información pero nuevamente hay una solución: Elíjanse los temas más interesantes y prepárense listas especializadas en esos temas. Una revisión diaria o semanal, según el nivel de actividad, será suficiente y, si se escogen los miembros de las listas con cuidado, se puede mantener uno actualizado sobre cualquier tema imaginable. Ni que decir tiene que se pueden añadir o quitar miembros de las listas.

En resumen, hay buenas razones para recomendar a alguien que tenga una cuenta en Twitter: Es un recurso valioso para mantenerse informado casi sobre cualquier tema. Ahora viene la parte más difícil: ¿Cómo debe ser la interacción en Twitter?

Mucha gente simplemente se mantiene en silencio. Siguen las fuentes que consideran interesantes y se acabó. Es una buena opción si no hay intención de compartir contenido propio. Puede encontrarse gente que utiliza sus propios nombres mientras otros prefieren no estar identificados, especialmente si tienen intención de participar activamente en discusiones sobre temas que puedan ser controvertidos y ahí precisamente aparece el lado oscuro de Twitter, un lado oscuro muy difícil de separar de la parte positiva.

Twitter es muy rapido. Por ello, medios tradicionales como la radio o la televisión lo utilizan como forma de mantener el contacto con sus seguidores y es frecuente ver una línea en televisión con un flujo de mensajes en Twitter. Esto les da a los programas sensación de actualidad y, al mismo tiempo, le da relevancia a Twitter, tanto en sus aspectos positivos como en los negativos.

Una vez que Twitter aparece como algo relevante, mucha gente empieza a utilizar la red para sus propios objetivos. Por ejemplo, se utilizan cuentas falsas con bots diseñados para convertir cualquier tema de su elección en trending topic en cuestión de minutos. Cuando se actúa así, por supuesto, la información sobre la relevancia real de un tema está falseada porque hay gente dedicada activamente a esa falsificación y, por añadidura, no se necesita ser un gran experto en redes sociales para ello.

Ésta es una parte negativa pero hay algo aún peor: La interacción entre miembros de Twitter es muy animada. Es fácil identificar grupos -incluso hay aplicaciones que permiten hacerlo automáticamente- y hay una fuerte presión hacia la conformidad dentro de esos grupos. Sus miembros, buscando el aplauso de sus compañeros de grupo, presentan visiones cada vez más extremas sobre cualquier tema controvertido y las discusiones resultantes aparecen en los medios más tradicionales como tendencias confundiendo la caricatura Twitter con la imagen real de una sociedad, imagen que a su vez se ve afectada por la difusión de la caricatura como realidad.

Hay muchos ejemplos actuales pero el caso español y su situación política es paradigmático. Tenemos de todo: Bots convirtiendo cualquier cosa en trending topic y gente que va derivando hacia visiones cada vez más extremas en sus posiciones políticas, especialmente si se trata de cuentas no identificadas o se trata de líderes de opinión que no quieren decepcionar a su auditorio. Por añadidura, esto no es un efecto específicamente español sino que, si se sigue la campaña americana, se encuentran exactamente los mismos fenómenos: La velocidad de la interacción y la brevedad de los mensajes, sin mucho espacio para matices, pueden ser los factores determinantes de ese comportamiento.

En suma, Twitter es una herramienta valiosa para mantenerse actualizados sobre cualquier tema pero, al mismo tiempo, tiene facetas muy negativas cuya influencia trasciende Twitter. Estar dentro es positivo pero mantenerse activo es algo para pensárselo dos veces. Aceptar las tendencias que marca Twitter como reales es algo que debe evitarse y no sólo porque probablemente sean falsas sino porque, dándoles carta de naturaleza, se puede contribuir a que se conviertan en reales aunque originalmente no lo fueran. Quizás todos tenemos una tarea de evitar que eso ocurra porque, debido a la presión hacia la conformidad, suele ocurrir que la posición ganadora se le llevan precisamente las más impresentables tendencias y comentarios…sin distinción de adscripción ideológica o de cualquier otro tipo.

Big Aviation is still a game of two players

And one of them, Airbus,  is celebrating its birthday.

Years ago, three major players were sharing the market but, once McDonnell Douglas disappeared, big planes were made by one of them. Of course, we should not forget Antonov, whose 225 model is still the biggest plane in the world, some huge Tupolev and Lockheed Tristar but the first ones never went out of their home markets while Lockheed Tristar could be seen as a failed experiment from the manufacturer.

Airbus emphasizes its milestones in the timeline but, behind these, there is a flow marked by efficiency through I.T. use.

Airbus was the first civilian planes manufacturer having a big plane with a cockpit for only two people (A-310) and Airbus was the first civilian plane manufacturer to introduce widely fly-by-wire technology (the only previous exception was the Concorde). Finally, Airbus introduced the commonality concept allowing pilots from a model to switch very fast to a different model keeping the rating for both.

Boeing had a more conservative position: B757 and B767 appeared with only two people in the cockpit after being redesigned to compete with A-310. Despite the higher experience of Boeing in military aviation and, hence, in fly-by-wire technology, Boeing deferred for a long time the decision to include it in civilian planes and, finally, where Boeing lost the efficiency battle was when it appeared with a portfolio whose products were mainly unrelated while Airbus was immerse in its commonality model.

The only point where Boeing arrived before was in the use of twin planes for transoceanic flights through the ETOPS policy. Paradoxically the ones in the worst position were the two American companies that were manufacturing three engine planes, McDonnell Douglas and Lockheed instead of Airbus. That was the exception because, usually, Boeing was behind in the efficiency field.

Probably -and this is my personal bet- they try to build a family starting with B787. This plane should be for Boeing the A320 equivalent, that is, the starter of a new generation sharing many features.

As a proof of that more conservative position, Boeing kept some feedbacks that Airbus simply removed like, for instance, the feeling of the flight controls or the feedback from autopilot to throttle levers. Nobody questionned if this should be made and it was offered as a commercial advantage instead of a safety feature since it was not compulsory…actually, the differences among both manufacturers -accepted by the regulators as features independent of safety-  have been in the root of some events

Little-size Aviation is much more crowded and, right now, we have two new incomers from Russia and China (Sukhoi and Comac) including the possibility of an agreement among them to fight for the big planes market.

Anyway, that is still in the future. Big Aviation is still a game of two contenders and every single step in that game has been driven by efficiency. Some of us would like understability -in normal and abnormal conditions- to be among the priorities in future designs, whatever they come from the present contenders or from any newcomer.

Published in my Linkedin profile

Air Safety and Hacker Frame of Mind

If we ask anyone what a hacker is, we could get answers going from cyberpiracy, cyberdelincuency, cybersecurity…and any other cyberthing. However, it’s much more than that.

Hackers are classified depending of the “color of their hats”. White hat hacker means individual devoted to security, black hat hacker means cybercriminal and grey hat hacker means something in the middle. That can be interesting as a matter of curiosity but…what do they have in common? Furthermore, what do they have in common that can be relevant for Air Safety?

Simonyi, the creator of WYSIWYG, warned long ago about an abstraction scale that was adding more and more steps. Speaking about Information Technology, that means that programmers don’t program a machine. They instruct a program to make a program to be run by a machine. Higher programming levels mean longer distance from the real thing and more steps between the human action and the machine action.

Of course, Simonyi warned of this as a potential problem while he was speaking about Information Technology but…Information Technology is now ubiquitous and this problem can be found anywhere including, of course, Aviation.

We could say that any IT-intensive system has different layers and the number of layers defines how advanced the system is. So far so good, if we assume that there is a perfect correspondance between layers, that is, every layer is a symbolic representation of the former one and that representation should be perfect. That should be all…but it isn’t.

Every information layer that we put over the real thing is not a perfect copy -it should be nonsense- but, instead, it tries to improve something in safety, efficiency or, very often, it claims to be improving both. However, avoiding flaws in that process is something that is almost impossible. That is the point where problems start and when hacker-type knowledge and frame of mind should be highly desirable for a pilot.

The symbolic nature of IT-based systems makes its flaws to be hard to diagnose since their behavior can be very different to mechanic or electric systems. Hackers, good or bad, try to identify these flaws, that is, they are very conscious of this symbolic layer approach instead of assuming an enhanced but perfect representation of the reality below.

What means a hacker frame of mind as a way to improve safety? Let me show two examples:

  • From cinema: The movie “A beautiful mind”, devoted to John Nash and showing his mental health problems shows at a moment how and why he was able to control these problems: He was confusing reality and fiction until a moment where he found something that did not fit. It happened to be a little girl that, after many years, continued being a little girl instead of an adult woman. That gave him the clue to know which part of his life was created by his own brain.
  • From Air Safety: A reflection taken from the book “QF32” by Richard de Crespigny: Engine 4 was mounted to our extreme right. The fuselage separated Engine 4 from Engines 1 and 2. So how could shrapnel pass over or under the fuselage, then travel all that way and damage Engine 4? The answer is clear. It can’t. However, once arrived there, a finding appears crystal-clear: Information coming from the plane is not trustable because in any of the IT-layers the correspondance reality-representation has been lost.

Detecting these problems is not easy. It implies much more than operating knowledge and, at the same time, we know that nobody has full knowledge about the whole system but only partial knowledge. That partial knowledge should be enough to define key indicators -as it happens in the mentioned examples- to know when we work with information that should not be trusted.

The hard part of this: The indicators should not be permanent but adapted to every situation, that is, the pilot should decide about which indicator should be used in situations that are not covered by procedures. That should bring us to other issue: If a hacker frame of mind is positive for Air Safety, how to create, nurture and train it? Let’s use again the process followed by a hacker to become such a hacker:

First, hackers look actively for information. They don’t go to formal courses expecting the information to be given. Instead, they look for resources allowing them to increase their knowledge level. Then, applying this model to Aviation should suppose a wide access to information sources beyond the information provided in formal courses.

Second, hackers training is more similar to military training than academic training, that is, they fight to intrude or to defend a system and they show their skills by opposing an active enemy. To replay a model such as this, simulators should include situations that trainers can imagine. Then, the design should be much more flexible and, instead of simulators behaving as a plane is supposed to do, they should have room to include potential situations coming from information misrepresentation or from situations coming from automatic answers to defective sensors.

Asking for a full knowledge of all the information layers and their potential pitfalls can be utopic since nobody has that kind of knowledge, including designers and engineers. Everybody has a partial knowledge. Then, how can we do our best with this partial knowledge? Looking for a different frame of mind in involved people -mainly pilots- and providing the information and training resources that allow that frame of mind to be created and developed. That could mean a fully new training model.

Published originally in my Linkedin profile

Sterile discussions about competencies, Emotional Intelligence and others…

When «Emotional Intelligence» fashion arrived with Daniel Goleman, I was among the discordant voices affirming that the concept and, especially, the use of it, was nonsense. Nobody can seriously reject that personal features are a key for success or failure. If we want to call it Emotional Intelligence that’s fine. It’s a marketing born name not very precise but, anyway, we can accept it.

However, losing the focus is not acceptable…and some people lose the focus with statements like «80% of success is due to Emotional Intelligence, well above the percentage due to «classic» intelligence. We lose focus too with statements comparing competencies with academic degress and the role of each part in professional success. These problems should be analyzed in a different and simpler way: It’s a matter of sequence instead of percentage.

An easy example: What is more important for a surgeon to be successful? The academic degree or the skills shown inside the OR? Of course, this is a tricky question where the trick is highly visible. To enter the OR armed with an scalpel, the surgeon needs an academic recognition and/or a specific license. Hence, the second filter -skills- is applied over the ones who passed the first one -academic recognition- and we cannot compare in percentage terms skills and academic recognition.

Of course, this is an extreme situation but we can apply it to the concepts where some sterile discussions appear. Someone can perform well thank to Emotional Intelligence but the entrance to the field is guaranteed with intelligence in the most common used meaning. Could we say that, once passed an IQ threshold we should better improve our interaction skills than -if possible- improve 10 more IQ points? Possibly…but things don’t work that way, that is, we define the access level through a threshold value and performance with other criteria, always comparing people that share something: They all are above the threshold value. Then…how can I say «Emotional Intelligence is in the root of 80% of success»? It should be false but we can convert it into true by adding  «if the comparison is made among people whose IQ is, at least medium-high level». The problem is that, with this addition, it is not false anymore but this kind of statement should be a simple-mindedness proof.

We cannot compare the relative importance of two factors if one of them is referred to job access while the other is referred to job performance once in the job. It’s like comparing bacon with speed but using percentages to appear more «scientific».

Frederick W. Taylor: XXI Century Release

Any motivation expert, from time to time, devotes a part of his time to throw some stones to Frederick W. Taylor. It seems, from our present scope, that there are good reasons for the stoning: Strict splitting between planning and performing is against any idea considering human beings as something more than faulty mechanisms.

However, if we try to get the perspective that Taylor could have a century ago, things could change: Taylor made unqualified workers able to manufacture complex products. These products were far beyond the understanding capacity of those manufacturing them.

From that point of view, we could say that Taylor and his SWO meant a clear advance and Taylor cannot be dismissed with a high-level theoretical approach out of context.

Many things have happened since Taylor that could explain so different approach: The education of average worker, at least in advanced societies, grew in an amazing way. The strict division between design and performance could be plainly justified in Taylor time but it could be nonsense right now.

Technology, especially the information related, not only advanced. We could say that it was born during the second half of the past century, well after Taylor. Advances have been so fast that is hard finding a fix point or a context to evaluate its contribution: When something evolves so fast, it modifies the initial context and that removes the reference point required to evaluate the real value.

At the risk of being simplistic, we could say that technology gives us «If…Then» solutions. As technology power increases, situations that can be confronted through an «If…Then» solution are more and more complex. Some time ago, I received this splendid parody of a call-center that shows clearly what can happen if people work only with «If…Then» recipes, coming, in this case, from a screen:

http://www.youtube.com/watch?v=GMt1ULYna4o

Technology evolution again puts the worker -now with an education level far superior to the one available in Taylor age- in a role of performer of routines and instructions. We could ask why so old model is still used and we could find some answers:

  • Economics: Less qualified people using technology can perform more complex tasks. That means savings in training costs and makes turnover also cheaper since people are easier to replace.
  • Knowledge Ownership: People have a brain that can store knowledge. Regretfully, from the perspective of a company, they have also feet that can be used to bring the brain to other places. In other words, knowledge stored by persons is not owned by companies and, hence, they could prefer storing knowledge in processes and Information Systems managing them.
  • Functionality: People commit more mistakes, especially in these issues hard to convert into routines and required going beyond stored knowledge.

These points are true but, when things are seen that way, there is something clear: The relation between a company and people working there is strictly economical. Arie de Geus, in The living organization, said that the relation between a person and a company is economic but considering it ONLY economic is a big mistake.

Actually, using If…Then model as a way to make people expendable can be a way to guarantee a more relaxed present situation…at the price of questionning the future. Let’s see why:

  • If…Then recipes are supplied by a short number of suppliers working in every market and, of course, having clients who compete among them. Once reduced the human factor to the minimum…where is it going to be the difference among companies sharing the same Information Systems model?
  • If people are given stricly operative knowledge…how can we advance in this knowledge? Companies outsource their ability to create new knowledge that, again, remains in the hands of their suppliers of Information Systems and their ability to store more «If…Then» solutions.
  • What is the real capacity of the organization to manage unforeseen contingencies, if they have not been anticipated in the system design or, even worse, contingencies coming from the growing complexity of the system itself?

This is the overview. Taylorism without Taylor is much worse than the original model since it’s not justified by the context. Companies perform better and better some things that they already knew how to manage and, at the same time, it is harder and harder for them improving at things that previously were poorly performed. People, under this model, cannot work as an emergency resource. To do this, they need knowledge far beyond the operative level and capacity to operate without being very constrained by the system. Very often they miss both.

Jens Rasmussen, expert in Organization and Safety, gave a golden rule that, regretfully, is not met in many places: Operator has to be able to run cognitively the program that the system is performing. Features of present Information Systems could allow us working under sub-optimized environments: Instead of an internal logic that only the designer can understand -and not always- things running and keeping the Rasmussen rule would be very different.

The rationale about training and turnover costs would remain but advantages from ignoring it are too important to dismiss them. The sentence of De Geus is real and, furthermore, it has a very serious impact about how our organizations are going to be in the next future.

 

Del parado como del cerdo todo se aprovecha…por parte de algunos

Sé que la afirmación es cruel pero después de ver, entre otras cosas, cómo los partidos políticos y sindicatos roban fondos destinados a la formación de los desempleados o meten en EREs realizados por empresas en crisis a esbirros suyos que jamás habían trabajado ahí…¿qué otra cosa puede decirse?

Pues bien, esta misma mañana me llega una forma más entre las muchas e ingeniosas que hay de robar a los parados:

Una empresa con un nombre muy sonoro, naturalmente en inglés, busca colaboradores expertos a los que, a cambio de una tarjeta y el honor de utilizar su nombre al facturar cobra una cuota de entrada que varía entre 18 y 30.000 euros y, después, una cifra del orden del 10 al 30% sobre facturación.

Naturalmente, los clientes se los tiene que buscar su víctima y se supone que se le abrirán las puertas del Universo una vez que aparezca ante los potenciales clientes con tan prestigioso nombre en su tarjeta. Estas «empresas» además ofrecen a menudo los servicios de un call-center destinado a conseguir entrevistas de forma que no haya que ir a hacer ventas a puerta fría. También cobran por entrevista conseguida, tanto si es con el Director General como con el encargado de la limpieza…y lo mejor de todo: Es absolutamente legal con lo que este tipo de estafadores sin escrúpulos están saliendo como las setas en otoño.

¿No es bastante dura la situación de desempleo para, además, tener que estar atentos a no ser estafados por este tipo de carroñeros?

Human Resources and Mathematical Fictions

It is hard to find more discussed and less solved issues than how to quantify Human Resources. We have looked for tools to evaluate jobs, to evaluate performance and at what percentage objectives were met. Some people tried to quantify in percentage terms how and individual and a job fit and, even, many people tried to obtain the ROI over training. Someone recovered Q index, aimed to quantify speculative investments, to convert it into the main variable for Intellectual Capital measurement, etc..

 Trying to get everything quantified is so absurd as denying a priori any possibility of quantification. However, some points deserve to be clarified:

New economy is the new motto but measurement and control instruments and, above all, business mentality is defined by engineers and economists and, hence, organizations are conceived as machines that have to be designed, adjusted, repaired and measured. However, it is a common fact that rigor demanded about meeting objectives is not used in the definition of the indicators. That brought something that is called here Mathematical Fictions.

A basic design principle should be that any indicator can be more precise than the thing it tries to indicate whatever the number of decimal digits we could use. When someone insists in keeping a wrong indicator, consequences appear and they are never good:

  •  Management behavior is driver by an indicator that can be misguided due to sneaky type of the variable supposedly indicated. It is worth remembering what happened when some Governments decided that the main priority in Social Security was reducing the number of days in waiting lists instead of the fluffy “improving Public Health System”. A common misbehavior should be to give priority to less time consuming interventions to reduce the number of citizens delaying the most importan tones.
  • There is a development of measurement systems whose costs are not paid by the supposed improvement to get from them. In other words, control becomes an objective instead of a vehicle since control advantages do not cover costs of building and maintenance of the control. For instance, some companies trying to control abuse in photocopies ask for a form for every single photocopy making the control much more expensive than the controlled resource.
  • Mathematical fictions appear when some weight variables that, in the best situation, are only useful for a situation and lose its value if the situation changes. Attemps relative to Intellectual Capital are a good example but we commit the same error if we try to obtain percents of people-job adjustment to use them as to foresee success in a recruiting process.
  • Above all, numbers are a language that is valid for some terrains but not for others. Written information is commonly rejected with “smart talk trap” arguments but the real fact is that we can perceive fake arguments easier in written or verbal statements than if they come wrapped in numbers. People use to be far less exigent about indicators design than about written reports.
  • Even though we always try to use numbers as “objective” indicators, the ability to handle these numbers by many people is surprisingly low. We do not need to speak about the journalist that wrote that Galapagos Islands are hundreds of thousands of kilometers far from Ecuador coast or the common mistake between American billion or European billion. We can show two easy examples about how numbers can lose any objectivity due to bad use:

After the accident of Concorde in Paris, 2001, media reported that it was the safest plane in the world. If we consider that, at that time, only fourteen planes of the type were flying instead of the thousands of not-so-exclusive planes, it is not surprising that an accident never happened before and, hence, nobody can say from it to be the safest plane. The sample was very short to say that.

Another example: In a public statement, the Iberia airline said that travelling by plane is 22 times safer than doing it by car. Does it mean that a minute spent in a plane is 22 times safer than a minute spent in a car? Far from it. This statement can be true or false depending of another variable: Exposure time. A Madrid-Barcelona flight lasts seven times less than a trip by car. However, if we try to contrast one hour inside a plane with an hour inside a car, results could be very far from these 22 times.

The only objective of these examples is showing how numbers can mislead too and we are less prepared to detect the trick than when we have to deal with written language.

These are old problems but –we have to insist- that does not mean they are solved and, perhaps, we should to arrive to the Savater idea in the sense that we do not deal with problems but with questions. Hence, we cannot expect a “solution” but contingent answer that never will close forever the question.

If we work with this in mind, measurement should acquire a new meaning. If we have contingent measurements and we are willing to build them seriously and to change them when they become useless, we could solve some –not all of them- problems linked to measurement. However, problems will arise when measurement is used to inform third parties and that could limit the possibility to change.

An example from Human Resources field can clarify this idea:

Some years ago, job evaluation systems had a real crisis. Competencies models came from this crisis but they have problems to for measurement. However, knowing why job evaluation systems started to be displaced is very revealing:

Even though there are not big differences among the most popular job evaluation systems, we will use Know-How, Problem Solving and Accountability, using a single table to compare different jobs in these three factors is brilliant. However, it has some problems hard to avoid:

  • Reducing to a single currency, the point, all the ratings coming from the three factors implies the existence of a “mathematical artifact” to weight the ratings and, hence, priming some factors over others.
  • If, after that, there are gross deviations from market levels, exceptions were required and these go directly against one of the main values that justified the system: Fairness.

Although these problems, job evaluation systems left an interesting legacy not very used: Before converting ratings into points, that is, before starting mathematical fictions, we have to rate every single factor. We have there a high quality information, for instance, to plan professional paths. A 13 points difference does not explain anything but a difference between D and E, if they are clearly defined, are a good index for a Human Resources manager.

If that is so…why is unused this potential of the system? There is an easy answer: Because job evaluation systems have been used as a salary negotiation tool and that brings another problem: Quantifiers have a bad design and, furthermore, they have been used for goals different from the original one.

The use of mix comittees for salary bargaining, among other factors, has nullified the analytical potential of job evaluation systems. Once a job is rated in a way, it is hard to know if this rating is real or it comes from the vagaries of the bargaining process.

While job evaluation remained as an internal tool of Human Resources area, it worked fine. If a system started to work poorly, it could be ignored or changed. However, if this system starts to be a main piece in the bargaining, it losses these features and, hence, its use as a Human Resources tool dissapears.

Something similar happens if we speak about Balanced Scorecard or Intellectual Capital. If we analyze both models, we’ll find that there is only a different variable and a different emphasis: We could say, without bending too much the concepts, that the Kaplan and Norton model is equal to Intellectual Capital plus financial side but there is another difference more relevant:

Balanced Scorecard is conceived as a tool for internal control. That implies that changes are easy while Intellectual Capital was created to give information to third parties. Hence, measurement has to be more permanent, less flexible and…less useful.

Actually, there are many examples to be used where the double use of a tool nullifies at least another one. The same idea of “Double Accounting” implies criticism. However, pretending that a system designed to give information to third parties can be, at the same time and with the same criteria, an effective tool for control, is quite near to ScFi.

Competencies systems have too its own part of mathematical fiction. It is hard to créate a system able to capture all the competencies and to avoid overlapping among them. If this is already hard…how is it possible to weight variables to define job-occupant adjustment? How many times are we evaluating the same thing under different names? When can we weight a competence? Is this value absolute or should it depend on contingencies? Summarizing….is it not a mathematical nonsense aimed to get a look of objectivity and, just-in-case, to justify a mistake?

This is not a declaration against measurement and, even less, against mathematics but against the symplistic use of it. “Do it as simple as possible but no more” is a good idea that is often forgotten.

Many of the figures that we use, not only in Human Resources, are real fiction ornated with a supposed objectivity coming from the use of a numeric language whose drawbacks are quite serious. Numeric language can be useful to write a symphony but nobody would use it to compose poetry (except if someone decides to use the cheap trick of converting letters into numbers) and, however, there is a general opinion about numbers as universal language or, as Intellectual Capital starters said, “numbers are the commonly accepted currency in the business language”.

We need to show not only momentaneous situations but dynamics and how to explain them. That requires written explanations that, certainly, can misguide but, at least, we are better equipped to detect it than if it come wrapped in numbers.