
\begin{slide}[toc=Ep/Con]{Error Potential/ Consequence Distributions}
Log the (CO1,EP1) values calculated by SILAP for different MB1 subsets

~\hrule~

\twocolumn{
265 records (eo2):

\includegraphics[width=2in]{eo2.er.eps}

93 records (xf3):

\includegraphics[width=2in]{xf3.er.eps}

}{
57 records (go4):

\includegraphics[width=2in]{go4.er.eps}

20 records (gs1):

\includegraphics[width=2in]{gs1.er.eps}


}

Comment: 
\bi
\item
in the majority of cases, the MB1 data set
does {\em not} select for $CO1\ge 4$  or $EP1\ge 4$
\ei

\end{slide}

\begin{slide}[toc=Rx + Treatment]{Diagnosis and Treatment}
\begin{itemize}
\item There is a bias in the WBS task selection:
\bi
\item Most tasks need  $CO1\ge 4$  or $EP1\ge 4$.
\ei
\item Diagnosis: the current SILAP/WBS selection tool differentiates
{\em hard problems};
\bi
\item But task selection is very insensitive to {\em ordinary problems}
$CO1< 4$  or $EP1< 4$.
\ei
\item So, treatment option one:
\bi
\item Applied one-size-fits-all WBS tasks to ``ordinary'' projects;
\item Reserve SILAP for ``hard'' projects.
\ei

\item Treatment option two: modify SILAP/WBS
    \bi
     \item Take the time to explore ``ordinary projects''
    \item How do they differ? What should we do about them?
 
    \ei
\item Option two is preferred....
   \bi
   \item If it is desired to optimize the day-to-day running of
routine IV\&V (which, according to MB1, is the norm)
   \ei
\end{itemize}

\end{slide}
\begin{slide}{But where's the AI?}

\begin{itemize}
\item
Coming, once LINKER gets on-line
\item
Or, once SILAP2 is available, we can return to Q3,Q4 (right connections?, right weights?).
\item
But its no surprise that an AI hacker (me) performed the above analysis
\begin{itemize}
\item
 AI is about
functionality and exploratory programming. 
\item It is about bottom-up design
and the building of ambitions as greater behaviors can be demonstrated. 
\item
It is about treating a model (like SILAP) as a rat in a maze and watching it run.
\end{itemize}
\end{itemize}
\end{slide}


